sora-astro 0.3.2.post2
Stellar Occultation Library
License: MIT
Requires Python: <4,>=3.11
Keywords: science, astronomy, occultation

SORA
====

PACKAGE DESCRIPTION
-------------------

SORA is the acronym for *Stellar Occultation Reduction and Analysis*.
It is a library developed in Python3 with the tools to analyze stellar
occultation data. It is based on Astropy functions and Classes.
**Discover the full documentation at https://sora.readthedocs.io/**

A stellar occultation occurs when a solar system object passes in front
of a star for an observer on Earth, and its shadow causes a temporary
drop in the observed flux of the star. This technique allows the
determination of sizes and shapes with kilometre precision and to obtain
characteristics of the object, such as its albedo, the presence of an
atmosphere, rings, jets, or other structures around the body or even
the detection of topographic features (Sicardy et al. 2011, 2016,
Braga-Ribas et al. 2013, 2014, 2019, 2023 Dias-Oliveira et al., 2015, 2017,
Benedetti-Rossi et al., 2016, 2019, Ortiz et al., 2015, 2017, 2020, 2023,
Leiva et al., 2017, Bérard et al., 2017, Morgado et al., 2019, 2022a, 2022b, 2023, 
Gomes-Júnior et al., 2020, Souami et al., 2020, Santos-Sanz et al., 2021, 2023,
Rommel et al., 2020, 2023, Pereira et al., 2023).

SORA is a Python-based, object-oriented library for optimal analysis of
stellar occultation data. The user can use this package to build pipelines
to analyse their stellar occultation’s data. It includes processes starting
on the prediction of such events to the resulting size, shape and position of
the Solar System object. The main modules available at version 0.2
are: **star**, **body**, **observer**, **spacecraft**, **lightcurve**, **chord** 
and **occultation**. It is important to note that new modules and other
improvements and implementations can be available in future versions.

AUTHORS
-------

Altair R. Gomes-Júnior (1, 2, 3),
Bruno E. Morgado (4, 3, 5),
Rodrigo C. Boufleur (5, 3),
Gustavo Benedetti-Rossi (2, 3),
Flavia L. Rommel (6, 5, 3),
Martin B. Huarca (3, 5)
Chrystian L. Pereira (5, 3)
Giuliano Margoti (6, 3)

(1) UFU - Federal University of Uberlândia, Physics Institute, Av. João Naves de Ávila 2121, Uberlândia, MG 38408-100, Brazil</br>
(2) UNESP - São Paulo State University, Grupo de Dinâmica Orbital e Planetologia, Guaratinguetá, SP 12516-410, Brazil</br>
(3) Laboratório Interinstitucional de e-Astronomia - LIneA and INCT do e-Universo, Rua Gal. José Cristino 77, Rio de Janeiro, RJ 20921-400, Brazil</br>
(4) Universidade Federal do Rio de Janeiro - Observatório do Valongo, Ladeira Pedro Antônio 43, CEP 20.080-090, Rio de Janeiro, Brazil</br>
(5) Observatório Nacional/MCTIC, R. General José Cristino 77, Rio de Janeiro, RJ 20.921-400, Brazil</br>
(6) Federal University of Technology - Paraná (UTFPR/DAFIS), Rua Sete de Setembro, 3165, CEP 80230-901, Curitiba, PR, Brazil</br>

CITATION
--------

SORA is a free software, and we kindly ask users that make use of it (or of part of it), especially in projects that results in scientific publications, to include the following citation:

::

    Gomes-Júnior et al. (2022). SORA: Stellar occultation reduction and analysis.
    MNRAS, Volume 511, Issue 1, March 2022, Pages 1167–1181
    DOI: 10.1093/mnras/stac032


The scientific documentation of SORA is described in the paper available on Monthly Notices
of the Royal Astronomical Society.

SYSTEM REQUIREMENTS AND INSTALLATION
------------------------------------

SORA was developed in Python 3.7 and requires the following packages:

-  Astropy (4.3.1): For astronomical related functions, mainly coordinates and time.

-  Astroquery (0.4.6): To query astronomical database as JPL and Vizier.

-  Matplotlib (3.5.3): For easy and beautiful plots.

-  NumPy (1.21): Otimized mathematical functions.

-  SciPy (1.7.1): Otimized functions for mathematics, science, and engineering.

-  SpiceyPy (6.0.0): SPICE/NAIF functions in python.

-  PyERFA (2.0): Python wrapper for the ERFA library based on the SOFA library.

-  Cartopy (0.21): Geospatial data processing to produce maps.

-  Shapely (2.0.1): Package for set-theoretic analysis and manipulation of planar features.

-  Tqdm (4.64): Creates Progress bar.

The user can install SORA and most of its requirements using **pip**, only
Cartopy should be installed from conda afterwards.

```shell
pip install sora-astro
conda install -c conda-forge cartopy
```

If you are a GitHub user, you can also use:

```shell
git clone https://github.com/riogroup/SORA.git
cd SORA
pip install .
conda install -c conda-forge cartopy
```

For a better experience with SORA, we recommend the use of [Jupyter]. The creation of a dedicated Conda environment for SORA is suggested to avoid requirement issues.

Acknowledgements
----------------

The SORA package is hosted on a GitHub repository. It was developed with support
of the LuckyStar, that agglomerates the efforts of the Paris, Granada, and Rio
teams. The LuckyStar is funded by the ERC (European Research Council)
under the European Community’s H2020 (2014-2020/ERC Grant Agreement No. 669416). Also,
this project is supported by LIneA (Laboratório Interinstitucional de e-Astronomia),
INCT do e-Universo (CNPQ grants 465376/2014-2), by FAPESP (proc. 2018/11239-8), by CNPQ
(proc. 300472/2020-0, 150612/2020-6), and by CAPES-PRINT/UNESP (88887.571156/2020-00)
in Brazil.

The Paris, Granada, and Rio teams are professionals astronomers affiliated mainly in the following
institutions:

* LESIA - Observatoire de Paris, France;
* Institut Polytechnique des Sciences Avancées, France;
* IMCCE - Observatoire de Paris, France;
* Instituto de Astrofísica de Andalucía, Spain;
* Laboratório Interinstitucional de e-Astronomia, Brazil;
* INCT do e-Universo, Brazil;
* Observatório Nacional/MCTI, Brazil;
* Federal University of Technology - Paraná, Brazil;
* UNESP - São Paulo State University, Brazil;
* Universidade Federal do Rio de Janeiro - Observatório do Valongo, Brazil;
* Federal University of Uberlândia, Brazil;