semvec/pypi-packages huggingface dataset:
ironman-package 1.1.0
Joint fit Rossiter-McLaughlin data with photometry and out-of-transit radial velocities
License: MIT
Requires Python: >=3.6
Keywords: Astronomy, Obliquities, Radial Velocities

# ironman

ironman is a Python package for jointly fitting in-transit and out-of-transit radial velocities with photometry. Its main objective is measuring stellar obliquities using the Rossiter-McLaughlin effect.

# Installation

You can install ironman with pip

```
pip install ironman-package
```
Or cloning the repository

```
git clone https://github.com/jiespinozar/ironman
cd ironman
pip install .
```

# Examples

To see examples of the usage of this module, see the example notebooks in the Examples folder.

- Example 1: How to fit data with ironman (sky-projected obliquity)
- Example 2: How to simulate data (e.g., for proposals)
- Example 3: How to fit data with ironman (true 3D obliquity)

# Dependencies

- rmfit (pip install rmfit)
- numpy (pip install numpy)
- scipy (pip install scipy)
- pandas (pip install pandas)
- batman-package (pip install batman-package)
- dynesty (pip install dynesty)
- astropy (pip install astropy)

# Citation

If you use this code, please cite [Espinoza-Retamal et al. 2024](https://ui.adsabs.harvard.edu/abs/2024arXiv240618631E/abstract)

If you use the RM fitting capability, please cite [Stefansson et al. 2022](https://ui.adsabs.harvard.edu/abs/2022ApJ...931L..15S/abstract) and [Hirano et al. 2010](https://ui.adsabs.harvard.edu/abs/2010ApJ...709..458H/abstract)

If you use the transit fitting capability, please cite [Kreidberg et al. 2015](https://ui.adsabs.harvard.edu/abs/2015ascl.soft10002K/abstract)

If you use the RV fitting capability, please cite [Fulton et al. 2018](https://ui.adsabs.harvard.edu/abs/2018PASP..130d4504F/abstract)
geestac 0.0.1
Google Earth Engine STAC
License: MIT
Requires Python: >=3.10
Keywords: Google Earth Engine, Python, STAC, geetools, skeleton


Google Earth Engine STAC (geestac)
##################################

.. |license| image:: https://img.shields.io/badge/License-MIT-yellow.svg?logo=opensourceinitiative&logoColor=white
    :target: LICENSE
    :alt: License: MIT

.. |commit| image:: https://img.shields.io/badge/Conventional%20Commits-1.0.0-yellow.svg?logo=git&logoColor=white
   :target: https://conventionalcommits.org
   :alt: conventional commit

.. |ruff| image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
   :target: https://github.com/astral-sh/ruff
   :alt: ruff badge

.. |prettier| image:: https://img.shields.io/badge/code_style-prettier-ff69b4.svg?logo=prettier&logoColor=white
   :target: https://github.com/prettier/prettier
   :alt: prettier badge

.. |pre-commmit| image:: https://img.shields.io/badge/pre--commit-active-yellow?logo=pre-commit&logoColor=white
    :target: https://pre-commit.com/
    :alt: pre-commit

.. |pypi| image:: https://img.shields.io/pypi/v/geestac?color=blue&logo=pypi&logoColor=white
    :target: https://pypi.org/project/geestac/
    :alt: PyPI version

.. |build| image:: https://img.shields.io/github/actions/workflow/status/fitoprincipe/geestac/unit.yaml?logo=github&logoColor=white
    :target: https://github.com/fitoprincipe/geestac/actions/workflows/unit.yaml
    :alt: build

.. |coverage| image:: https://img.shields.io/codecov/c/github/fitoprincipe/geestac?logo=codecov&logoColor=white
    :target: https://codecov.io/gh/fitoprincipe/geestac
    :alt: Test Coverage

.. |docs| image:: https://img.shields.io/readthedocs/geestac?logo=readthedocs&logoColor=white
    :target: https://geestac.readthedocs.io/en/latest/
    :alt: Documentation Status

|license| |commit| |ruff| |prettier| |pre-commmit| |pypi| |build| |coverage| |docs|

Overview
--------

This packages provides an easy and straightforward way of getting Google Earth
Engine STAC information.

To take fully advantage of this package is recommended to use it in runtime
due to `lazy evaluation <https://en.wikipedia.org/wiki/Lazy_evaluation>`__

Installation
------------

.. code-block:: bash

    pip install geestac

Usage
-----

.. code-block:: python

    from geestac import eecatalog

    # a lazy object does not contain the complete data but only the reference (name and url)
    landsat_lazy = eecatalog.LANDSAT

    # to fetch all data you need to call it
    landast = eecatalog.LANDSAT()

    # if you do this in runtime, the `landsat` object contains all datasets as attributes
    # if you don't do it in runtime you won't be able to see the datasets (attributes)

    # it works the same with datasets
    # lazy dataset
    l9_lazy = landsat.LC09_C02_T1
    # fetch L9 data
    l9 = landsat.LC09_C02_T1()


Credits
-------
Author: Rodrigo E. Principe

This package was created with `Copier <https://copier.readthedocs.io/en/latest/>`__ and the `@12rambau/pypackage <https://github.com/12rambau/pypackage>`__ 0.1.16 project template.