emantis 1.2.2

Description

e-MANTIS is a python package containing emulators providing theoretical predictions for the nonlinear large-scale structure formation in the context of alternative dark energy and gravity theories. It uses Gaussian processes to perform a fast and accurate interpolation between the outputs of high resolution cosmological \(N\)-body simulations. The emulator supports multiple cosmological models and observables. It is divided in multiple modules, each one focusing on a particular type of observable. Currently, e-MANTIS provides emulators for the following quantities:

• Matter power spectrum boost in f(R) gravity, described in: The e-MANTIS emulator: fast predictions of the nonlinear matter power spectrum in f(R)CDM cosmology.

• Halo mass function in f(R)CDM and wCDM cosmologies, described in: The e-MANTIS emulator: fast and accurate predictions of the halo mass function in f(R)CDM and wCDM cosmologies.

Please cite the corresponding papers if you use e-MANTIS in your work.

This project is under constant development. More observables and cosmological models will be added in the future. Stay tuned!

Installation

You can install the python package from PyPI via pip:

pip install emantis

Or you can directly clone our public repository and install it from source:

git clone https://gitlab.obspm.fr/e-mantis/e-mantis.git
cd e-mantis
pip install [-e] .

It requires a python version >= 3.10.

Post-installation

The emulators shipped with e-MANTIS need to be trained before they can provide predictions. This will be done automatically and on-the-fly the first time you use each emulator.

Alternatively, we provide a CLI utility to train all emulators at once:

emantis-train

This should not take more than a couple of minutes.

The trained emulators are saved to disk, using the pickle protocol, ready for future usage. Major changes in the versions of python, e-MANTIS, or some of its main dependencies, such as numpy, scipy, or scikit-learn, might break the compatibility with previously trained emulators. In such case, the emulators will be retrained automatically on-the-fly. You can also retrain them manually using the CLI utility.

Documentation and usage

The up-to-date documentation for this project (with code examples and a detailed API) is available here.

Licence

Copyright (C) 2023 Iñigo Sáez-Casares

inigo.saez-casares@obspm.fr

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.