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;
Raw data
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"description": "SORA\n====\n\nPACKAGE DESCRIPTION\n-------------------\n\nSORA is the acronym for *Stellar Occultation Reduction and Analysis*.\nIt is a library developed in Python3 with the tools to analyze stellar\noccultation data. It is based on Astropy functions and Classes.\n**Discover the full documentation at https://sora.readthedocs.io/**\n\nA stellar occultation occurs when a solar system object passes in front\nof a star for an observer on Earth, and its shadow causes a temporary\ndrop in the observed flux of the star. This technique allows the\ndetermination of sizes and shapes with kilometre precision and to obtain\ncharacteristics of the object, such as its albedo, the presence of an\natmosphere, rings, jets, or other structures around the body or even\nthe detection of topographic features (Sicardy et al. 2011, 2016,\nBraga-Ribas et al. 2013, 2014, 2019, 2023 Dias-Oliveira et al., 2015, 2017,\nBenedetti-Rossi et al., 2016, 2019, Ortiz et al., 2015, 2017, 2020, 2023,\nLeiva et al., 2017, B\u00e9rard et al., 2017, Morgado et al., 2019, 2022a, 2022b, 2023, \nGomes-J\u00fanior et al., 2020, Souami et al., 2020, Santos-Sanz et al., 2021, 2023,\nRommel et al., 2020, 2023, Pereira et al., 2023).\n\nSORA is a Python-based, object-oriented library for optimal analysis of\nstellar occultation data. The user can use this package to build pipelines\nto analyse their stellar occultation\u2019s data. It includes processes starting\non the prediction of such events to the resulting size, shape and position of\nthe Solar System object. The main modules available at version 0.2\nare: **star**, **body**, **observer**, **spacecraft**, **lightcurve**, **chord** \nand **occultation**. It is important to note that new modules and other\nimprovements and implementations can be available in future versions.\n\nAUTHORS\n-------\n\nAltair R. Gomes-J\u00fanior (1, 2, 3),\nBruno E. Morgado (4, 3, 5),\nRodrigo C. Boufleur (5, 3),\nGustavo Benedetti-Rossi (2, 3),\nFlavia L. Rommel (6, 5, 3),\nMartin B. Huarca (3, 5)\nChrystian L. Pereira (5, 3)\nGiuliano Margoti (6, 3)\n\n(1) UFU - Federal University of Uberl\u00e2ndia, Physics Institute, Av. Jo\u00e3o Naves de \u00c1vila 2121, Uberl\u00e2ndia, MG 38408-100, Brazil</br>\n(2) UNESP - S\u00e3o Paulo State University, Grupo de Din\u00e2mica Orbital e Planetologia, Guaratinguet\u00e1, SP 12516-410, Brazil</br>\n(3) Laborat\u00f3rio Interinstitucional de e-Astronomia - LIneA and INCT do e-Universo, Rua Gal. Jos\u00e9 Cristino 77, Rio de Janeiro, RJ 20921-400, Brazil</br>\n(4) Universidade Federal do Rio de Janeiro - Observat\u00f3rio do Valongo, Ladeira Pedro Ant\u00f4nio 43, CEP 20.080-090, Rio de Janeiro, Brazil</br>\n(5) Observat\u00f3rio Nacional/MCTIC, R. General Jos\u00e9 Cristino 77, Rio de Janeiro, RJ 20.921-400, Brazil</br>\n(6) Federal University of Technology - Paran\u00e1 (UTFPR/DAFIS), Rua Sete de Setembro, 3165, CEP 80230-901, Curitiba, PR, Brazil</br>\n\nCITATION\n--------\n\nSORA 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:\n\n::\n\n Gomes-J\u00fanior et al. (2022). SORA: Stellar occultation reduction and analysis.\n MNRAS, Volume 511, Issue 1, March 2022, Pages 1167\u20131181\n DOI: 10.1093/mnras/stac032\n\n\nThe scientific documentation of SORA is described in the paper available on Monthly Notices\nof the Royal Astronomical Society.\n\nSYSTEM REQUIREMENTS AND INSTALLATION\n------------------------------------\n\nSORA was developed in Python 3.7 and requires the following packages:\n\n- Astropy (4.3.1): For astronomical related functions, mainly coordinates and time.\n\n- Astroquery (0.4.6): To query astronomical database as JPL and Vizier.\n\n- Matplotlib (3.5.3): For easy and beautiful plots.\n\n- NumPy (1.21): Otimized mathematical functions.\n\n- SciPy (1.7.1): Otimized functions for mathematics, science, and engineering.\n\n- SpiceyPy (6.0.0): SPICE/NAIF functions in python.\n\n- PyERFA (2.0): Python wrapper for the ERFA library based on the SOFA library.\n\n- Cartopy (0.21): Geospatial data processing to produce maps.\n\n- Shapely (2.0.1): Package for set-theoretic analysis and manipulation of planar features.\n\n- Tqdm (4.64): Creates Progress bar.\n\nThe user can install SORA and most of its requirements using **pip**, only\nCartopy should be installed from conda afterwards.\n\n```shell\npip install sora-astro\nconda install -c conda-forge cartopy\n```\n\nIf you are a GitHub user, you can also use:\n\n```shell\ngit clone https://github.com/riogroup/SORA.git\ncd SORA\npip install .\nconda install -c conda-forge cartopy\n```\n\nFor 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.\n\nAcknowledgements\n----------------\n\nThe SORA package is hosted on a GitHub repository. It was developed with support\nof the LuckyStar, that agglomerates the efforts of the Paris, Granada, and Rio\nteams. The LuckyStar is funded by the ERC (European Research Council)\nunder the European Community\u2019s H2020 (2014-2020/ERC Grant Agreement No. 669416). Also,\nthis project is supported by LIneA (Laborat\u00f3rio Interinstitucional de e-Astronomia),\nINCT do e-Universo (CNPQ grants 465376/2014-2), by FAPESP (proc. 2018/11239-8), by CNPQ\n(proc. 300472/2020-0, 150612/2020-6), and by CAPES-PRINT/UNESP (88887.571156/2020-00)\nin Brazil.\n\nThe Paris, Granada, and Rio teams are professionals astronomers affiliated mainly in the following\ninstitutions:\n\n* LESIA - Observatoire de Paris, France;\n* Institut Polytechnique des Sciences Avanc\u00e9es, France;\n* IMCCE - Observatoire de Paris, France;\n* Instituto de Astrof\u00edsica de Andaluc\u00eda, Spain;\n* Laborat\u00f3rio Interinstitucional de e-Astronomia, Brazil;\n* INCT do e-Universo, Brazil;\n* Observat\u00f3rio Nacional/MCTI, Brazil;\n* Federal University of Technology - Paran\u00e1, Brazil;\n* UNESP - S\u00e3o Paulo State University, Brazil;\n* Universidade Federal do Rio de Janeiro - Observat\u00f3rio do Valongo, Brazil;\n* Federal University of Uberl\u00e2ndia, Brazil;\n",
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