minot: Modeling the ICM (Non-)thermal content and Observable prediction Tools

Software dedicated to provide a self-consistent modeling framework for the thermal and the non-thermal diffuse components in galaxy clusters, and provide multi-wavelenght observables predictions.

Overview of the physical processes and structure of the code

Figure 1. Overview of the parametrization, physical processes, and observables dependencies.

Figure 2. The structure of the code.

Content

The minot directory contains the main code, including:

model.py : main code that defines the class Cluster
model_admin.py : subclass that defines administrative tools
model_modpar.py : subclass that handles model parameters functions
model_phys.py : subclass that handles the physical properties of the cluster
model_obs.py : subclass that handles the observational properties of the cluster
model_plots.py : plotting tools for automatic outputs
model_title.py : title for the package
ClusterTools : Repository that gather several useful libraries

The root directory also provides a set of examples:

notebook : Repository where to find Jupyter notebook used for validation/example.

Environment

To be compliant with other softwares developed in parallel, the code was originally developed in python 2. Recently, the code was made compatible with python 3.

Installation

You can use pip to install the package:

pip install minot

Dependencies

The software depends on standard python packages:

astropy
numpy
scipy
matplotlib

But also:

ebltable (see https://github.com/me-manu/ebltable)
healpy (optional, see https://healpy.readthedocs.io/en/latest). Healpy is not automatically installed, but you can do it independently to benefit of a view functions that use healpy, but are not directly used in minot.

In the case of X-ray outputs, it will be necessary to have the XSPEC software installed independently (https://heasarc.gsfc.nasa.gov/xanadu/xspec/).

Encountered issues

Depending on the python version, the automatic installation of healpy does not work. As healpy is optional, it was removed from the dependencies and healpy can be installed independently if necessary.
For MAC-OS, in some version of python 2, the automatic installation of matplotlib may lead to an error related to the backend when importing matplotlib.pyplot. In this case, reinstalling matplotlib using conda, as conda install matplotlib should solve the problem.
The automatic installation of dependencies is sometimes misbehaving. In such case, you may just install the required packages independently:

conda install astropy

conda install numpy

conda install scipy

conda install matplotlib

Reference

In case you use minot in your research, you can cite R. Adam, H. Goksu, A. Leingärtner-Goth, et al. (2020) to acknowledge its use. The paper is availlable here and contains the full description of the code: https://ui.adsabs.harvard.edu/abs/2020arXiv200905373A/abstract. This also https://www.aanda.org/articles/aa/full_html/2020/12/aa39091-20/aa39091-20.html

History

Version 0.1.0 --> Initial release
Version 0.1.1 --> Correction of warnings and minor bugs
Version 1.1.2 --> Implement new universal profiles
Version 1.1.3 --> Exact UPP definition implemented; commenting updates

remi-adam/minot