=======
hierArc
=======
.. image:: https://img.shields.io/pypi/v/hierarc.svg
:target: https://pypi.python.org/pypi/hierarc
.. image:: https://github.com/sibirrer/hierarc/workflows/Tests/badge.svg
:target: https://github.com/sibirrer/hierarc/actions
.. image:: https://coveralls.io/repos/github/sibirrer/hierArc/badge.svg?branch=main
:target: https://coveralls.io/github/sibirrer/hierArc?branch=main
.. image:: https://readthedocs.org/projects/hierarc/badge/?version=latest
:target: https://hierarc.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat
:target: http://www.astropy.org
:alt: Powered by Astropy Badge
Hierarchical analysis of strong lensing systems to infer lens properties and cosmological parameters simultaneously.
The software is originated from `Birrer et al. 2020 <https://arxiv.org/abs/2007.02941>`_ and is in active development.
* Free software: BSD license
* Documentation: https://hierarc.readthedocs.io.
Features
--------
The software allows to fit lenses with measured time delays, imaging information, kinematics constraints and
standardizable magnifications with parameters described on the ensemble level.
Installation
------------
.. code-block:: bash
$ pip install hierarc --user
Usage
-----
The full analysis of `Birrer et al. 2020 <https://arxiv.org/abs/2007.02941>`_ is publicly available `at this TDCOSMO repository <https://github.com/TDCOSMO/hierarchy_analysis_2020_public>`_ .
A forecast based on hierArc is presented by `Birrer & Treu 2020 <https://arxiv.org/abs/2008.06157>`_
and the notebooks are available `at this repository <https://github.com/sibirrer/TDCOSMO_forecast>`_.
The extension to using hierArc with standardizable magnifications is presented by `Birrer et al. 2021 <https://arxiv.org/abs/2107.12385>`_
and the forecast analysis is publicly available `here <https://github.com/sibirrer/glSNe>`_.
For example use cases we refer to the notebooks of these analyses.
Credits
-------
Simon Birrer & the `TDCOSMO <http://tdcosmo.org>`_ team.
Please cite `Birrer et al. 2020 <https://arxiv.org/abs/2007.02941>`_ if you make use of this software for your research.
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"description": "=======\nhierArc\n=======\n\n\n.. image:: https://img.shields.io/pypi/v/hierarc.svg\n :target: https://pypi.python.org/pypi/hierarc\n\n.. image:: https://github.com/sibirrer/hierarc/workflows/Tests/badge.svg\n :target: https://github.com/sibirrer/hierarc/actions\n\n.. image:: https://coveralls.io/repos/github/sibirrer/hierArc/badge.svg?branch=main\n :target: https://coveralls.io/github/sibirrer/hierArc?branch=main\n\n.. image:: https://readthedocs.org/projects/hierarc/badge/?version=latest\n :target: https://hierarc.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. image:: http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat\n :target: http://www.astropy.org\n :alt: Powered by Astropy Badge\n\n\n\nHierarchical analysis of strong lensing systems to infer lens properties and cosmological parameters simultaneously.\n\nThe software is originated from `Birrer et al. 2020 <https://arxiv.org/abs/2007.02941>`_ and is in active development.\n\n* Free software: BSD license\n* Documentation: https://hierarc.readthedocs.io.\n\n\nFeatures\n--------\n\nThe software allows to fit lenses with measured time delays, imaging information, kinematics constraints and\nstandardizable magnifications with parameters described on the ensemble level.\n\nInstallation\n------------\n\n.. code-block:: bash\n\n $ pip install hierarc --user\n\n\nUsage\n-----\n\nThe full analysis of `Birrer et al. 2020 <https://arxiv.org/abs/2007.02941>`_ is publicly available `at this TDCOSMO repository <https://github.com/TDCOSMO/hierarchy_analysis_2020_public>`_ .\nA forecast based on hierArc is presented by `Birrer & Treu 2020 <https://arxiv.org/abs/2008.06157>`_\nand the notebooks are available `at this repository <https://github.com/sibirrer/TDCOSMO_forecast>`_.\nThe extension to using hierArc with standardizable magnifications is presented by `Birrer et al. 2021 <https://arxiv.org/abs/2107.12385>`_\nand the forecast analysis is publicly available `here <https://github.com/sibirrer/glSNe>`_.\nFor example use cases we refer to the notebooks of these analyses.\n\n\n\nCredits\n-------\n\nSimon Birrer & the `TDCOSMO <http://tdcosmo.org>`_ team.\n\nPlease cite `Birrer et al. 2020 <https://arxiv.org/abs/2007.02941>`_ if you make use of this software for your research.\n\n\n",
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