S+LEAF documentation#
S+LEAF is an open-source software that provides a flexible noise model with fast and scalable methods. It is largely inspired by the celerite / celerite2 model proposed by [1], [3]. In particular the modeling of gaussian processes is similar, and uses the same semiseparable matrices representation as celerite. S+LEAF extends the celerite model in several ways:
It allows to account for close to diagonal (LEAF) noises such as instrument calibration errors (see [2]).
It allows to model simulatenously several time series with the same Gaussian processes and their derivatives (see [4]).
It provides an efficient implementation of the FENRIR stellar activity model (see [5])
Please cite [2], [4], and/or [5] if you use S+LEAF in a publication.
Installation#
Using conda#
The S+LEAF package can be installed using conda with the following command:
conda install -c conda-forge spleaf
Using pip#
It can also be installed using pip with:
pip install spleaf
Usage#
S+LEAF covariance matrices are generated using the spleaf.cov.Cov class. The covariance matrix is modeled as the sum of different components (or terms), which split into two categories: noise terms and kernel terms (gaussian processes). See the API reference for a list of available terms.
The low level implementation of S+LEAF matrices as defined by [2] is available as the spleaf.Spleaf class, but one typically does not need to directly deal with it.
Examples#
API Reference#
Contribute#
Everyone is welcome to open issues and/or contribute code via pull-requests. A SWITCH edu-ID account is necessary to sign in to https://gitlab.unige.ch. If you don’t have an account, you can easily create one at https://eduid.ch. Then you can sign in to https://gitlab.unige.ch by selecting “SWITCH edu-ID” as your organisation.