Metadata-Version: 1.1
Name: lenstronomy
Version: 1.9.1
Summary: Strong lens modeling package.
Home-page: https://github.com/sibirrer/lenstronomy
Author: Simon Birrer
Author-email: sibirrer@gmail.com
License: MIT
Download-URL: https://github.com/sibirrer/lenstronomy/archive/1.9.1.tar.gz
Description: ====================================================
        lenstronomy - gravitational lensing software package
        ====================================================
        
        
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        ``lenstronomy`` is a multi-purpose package to model strong gravitational lenses. The software package is presented in
        `Birrer & Amara 2018 <https://arxiv.org/abs/1803.09746v1>`_ and `Birrer et al. 2021 <https://joss.theoj.org/papers/10.21105/joss.03283>`_ , and is based on `Birrer et al 2015 <http://adsabs.harvard.edu/abs/2015ApJ...813..102B>`_.
        ``lenstronomy`` finds application for time-delay cosmography and measuring
        the expansion rate of the Universe, for quantifying lensing substructure to infer dark matter properties, morphological quantification of galaxies,
        quasar-host galaxy decomposition and much more.
        A (incomplete) list of publications making use of lenstronomy can be found `at this link <https://github.com/sibirrer/lenstronomy/blob/main/PUBLISHED.rst>`_.
        
        
        The development is coordinated on `GitHub <https://github.com/sibirrer/lenstronomy>`_ and contributions are welcome.
        The documentation of ``lenstronomy`` is available at `readthedocs.org <http://lenstronomy.readthedocs.org/>`_ and
        the package is distributed over `PyPI <https://pypi.python.org/pypi/lenstronomy>`_.
        ``lenstronomy`` is an `affiliated package <https://www.astropy.org/affiliated/>`_ of `astropy <https://www.astropy.org/>`_.
        
        
        
        Installation
        ------------
        
        .. code-block:: bash
        
            $ pip install lenstronomy --user
        
        
        Specific instructions for settings and installation requirements for special cases that can provide speed-ups,
        we refer to the `documentation <https://lenstronomy.readthedocs.io/en/latest/installation.html>`_ page.
        
        
        
        Getting started
        ---------------
        
        The `starting guide jupyter notebook <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/starting_guide.ipynb>`_
        leads through the main modules and design features of ``lenstronomy``. The modular design of ``lenstronomy`` allows the
        user to directly access a lot of tools and each module can also be used as stand-alone packages.
        
        If you are new to gravitational lensing, check out the `mini lecture series <https://github.com/sibirrer/strong_lensing_lectures>`_ giving an introduction to gravitational lensing
        with interactive Jupyter notebooks in the cloud.
        
        
        
        Example notebooks
        -----------------
        
        We have made an extension module available at `https://github.com/sibirrer/lenstronomy_extensions <https://github.com/sibirrer/lenstronomy_extensions>`_.
        You can find simple examle notebooks for various cases. The latest versions of the notebooks should be compatible with the recent pip version of lenstronomy.
        
        * `Units, coordinate system and parameter definitions in lenstronomy <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/units_coordinates_parameters.ipynb>`_
        * `FITS handling and extracting needed information from the data prior to modeling <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/fits_handling.ipynb>`_
        * `Modeling a simple Einstein ring <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/simple_ring.ipynb>`_
        * `Quadrupoly lensed quasar modelling <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/quad_model.ipynb>`_
        * `Double lensed quasar modelling <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/double_model.ipynb>`_
        * `Time-delay cosmography <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/time-delay%20cosmography.ipynb>`_
        * `Source reconstruction and deconvolution with Shapelets <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/shapelet_source_modelling.ipynb>`_
        * `Solving the lens equation <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/lens_equation.ipynb>`_
        * `Multi-band fitting <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/multi_band_fitting.ipynb>`_
        * `Measuring cosmic shear with Einstein rings <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/EinsteinRingShear_simulations.ipynb>`_
        * `Fitting of galaxy light profiles, like e.g. GALFIT <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/galfitting.ipynb>`_
        * `Quasar-host galaxy decomposition <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/quasar-host%20decomposition.ipynb>`_
        * `Hiding and seeking a single subclump <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/substructure_challenge_simple.ipynb>`_
        * `Mock generation of realistic images with substructure in the lens <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/substructure_challenge_mock_production.ipynb>`_
        * `Mock simulation API with multi color models <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/simulation_api.ipynb>`_
        * `Catalogue data modeling of image positions, flux ratios and time delays <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/catalogue%20modelling.ipynb>`_
        * `Example of numerical ray-tracing and convolution options <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/lenstronomy_numerics.ipynb>`_
        * `Simulated lenses with populations generated by SkyPy <https://github.com/sibirrer/lenstronomy_extensions/blob/main/lenstronomy_extensions/Notebooks/skypy_lenstronomy.ipynb>`_
        
        
        
        Affiliated packages
        -------------------
        Multiple affiliated packages that make use of lenstronomy can be found `here <https://lenstronomy.readthedocs.io/en/latest/affiliatedpackages.html>`_
        (not complete) and further packages are under development by the community.
        
        
        Mailing list and Slack channel
        ------------------------------
        
        You can join the ``lenstronomy`` mailing list by signing up on the
        `google groups page <https://groups.google.com/forum/#!forum/lenstronomy>`_.
        
        
        The email list is meant to provide a communication platform between users and developers. You can ask questions,
        and suggest new features. New releases will be announced via this mailing list.
        
        We also have a `Slack channel <https://lenstronomers.slack.com>`_ for the community.
        Please send me an `email <sibirrer@gmail.com>`_ such that I can add you to the channel.
        
        
        If you encounter errors or problems with ``lenstronomy``, please let us know!
        
        
        
        Contribution
        ------------
        Check out the `contributing page <https://lenstronomy.readthedocs.io/en/latest/contributing.html>`_
        and become an author of ``lenstronomy``! A big shutout to the current `list of contributors and developers <https://lenstronomy.readthedocs.io/en/latest/authors.html>`_!
        
        
        
        
        Shapelet reconstruction demonstration movies
        --------------------------------------------
        
        We provide some examples where a real galaxy has been lensed and then been reconstructed by a shapelet basis set.
        
        * `HST quality data with perfect knowledge of the lens model <http://www.astro.ucla.edu/~sibirrer/video/true_reconstruct.mp4>`_
        * `HST quality with a clump hidden in the data <http://www.astro.ucla.edu/~sibirrer/video/clump_reconstruct.mp4>`_
        * `Extremely large telescope quality data with a clump hidden in the data <http://www.astro.ucla.edu/~sibirrer/video/TMT_high_res_clump_reconstruct.mp4>`_
        
        
        
        Attribution
        -----------
        The design concept of ``lenstronomy`` is reported by `Birrer & Amara 2018 <https://arxiv.org/abs/1803.09746v1>`_.
        The current JOSS software publication is presented by `Birrer et al. 2021 <https://joss.theoj.org/papers/10.21105/joss.03283>`_.
        Please cite these two publications when you use lenstronomy in a publication and link to `https://github.com/sibirrer/lenstronomy <https://github.com/sibirrer/lenstronomy>`_.
        Please also cite `Birrer et al 2015 <http://adsabs.harvard.edu/abs/2015ApJ...813..102B>`_
        when you make use of the ``lenstronomy`` work-flow or the Shapelet source reconstruction and make sure to cite also
        the relevant work that was implemented in ``lenstronomy``, as described in the release paper and the documentation.
        Don't hesitate to reach out to the developers if you have questions!
        
Keywords: lenstronomy
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.6
