Metadata-Version: 1.1
Name: pypher
Version: 0.6.4
Summary: Python-based PSF Homogenization kERnels production
Home-page: http://pypher.readthedocs.org/en/latest/
Author: Alexandre Boucaud
Author-email: boucaud.alexandre@gmail.com
License: New BSD
Download-URL: https://git.ias.u-psud.fr/aboucaud/pypher/
Description: ====================================================
        PyPHER - Python-based PSF Homogenization kERnels
        ====================================================
        
        |pypi| |docs| |license| |doi| |travis|
        
        Compute an homogenization kernel between two PSFs.
        
        This code is well suited for PSF matching applications in both an astronomical or microscopy context.
        
        It has been developed as part of the ESA `Euclid <http://www.cosmos.esa.int/web/euclid>`_ mission and is currently being used for multi-band photometric studies of `HST <https://www.spacetelescope.org/>`_ (visible) and `Herschel <http://www.cosmos.esa.int/web/herschel/home>`_ (IR) data.
        
        :Paper: http://arxiv.org/abs/1609.02006
        :Documentation: https://pypher.readthedocs.io
        
        Features
        ========
        
        1. **Warp** (rotation + resampling) the PSF images (if necessary),
        2. **Filter** images in Fourier space using a regularized Wiener filter,
        3. **Produce** a homogenization kernel.
        
        **Note:** ``pypher`` needs the pixel scale information to be present in the FITS files. If not, use the provided ``addpixscl`` method to add this missing info.
        
        **Warning:** This code **does not**
        
            * interpolate NaN values (replaced by 0 instead),
            * center PSF images,
            * minimize the kernel size.
        
        
        Installation
        ============
        
        PyPHER works both with Python 2.7 and 3.4 or later and relies on `numpy <http://www.numpy.org/>`_, `scipy <http://www.scipy.org/>`_ and `astropy <http://www.astropy.org/>`_ libraries.
        
        Option 1: `Pip <https://pypi.python.org/pypi/pypher>`_
        ------------------------------------------------------
        
        .. code:: bash
        
            $ pip install pypher
        
        Option 2: from `source <https://git.ias.u-psud.fr/aboucaud/pypher>`_
        --------------------------------------------------------------------
        
        .. code:: bash
        
            $ git clone https://git.ias.u-psud.fr/aboucaud/pypher.git
            $ cd pypher
            $ python setup.py install
        
        
        Basic example
        =============
        
        .. code:: bash
        
            $ pypher psf_a.fits psf_b.fits kernel_a_to_b.fits -r 1.e-5
        
        This will create the desired kernel ``kernel_a_to_b.fits`` and a short
        log ``kernel_a_to_b.log`` with information about the processing.
        
        
        Acknowledging
        =============
        
        If you make use of any product of this code in a scientific publication,
        please consider acknowledging the work by citing the paper |arxiv| as
        well as the code itself |doi|.
        
        
        .. |pypi| image:: https://img.shields.io/pypi/v/pypher.svg
            :alt: Latest Version
            :scale: 100%
            :target: https://pypi.python.org/pypi/pypher
        
        .. |docs| image:: https://readthedocs.org/projects/pypher/badge/?version=latest
            :alt: Documentation Status
            :scale: 100%
            :target: https://pypher.readthedocs.org/en/latest/?badge=latest
        
        .. |license| image:: https://img.shields.io/badge/license-BSD-blue.svg?style=flat
            :alt: License type
            :scale: 100%
            :target: https://git.ias.u-psud.fr/aboucaud/pypher/blob/master/LICENSE
        
        .. |doi| image:: https://zenodo.org/badge/21241/aboucaud/pypher.svg
            :alt: DOI number
            :scale: 100%
            :target: https://zenodo.org/badge/latestdoi/21241/aboucaud/pypher
        
        .. |arxiv| image:: http://img.shields.io/badge/arXiv-1609.02006-yellow.svg?style=flat
             :alt: arXiv paper
             :scale: 100%
             :target: https://arxiv.org/abs/1609.02006
        
        .. |travis| image:: https://travis-ci.org/aboucaud/pypher.svg?branch=master
            :alt: Travis CI
            :scale: 100%
            :target: https://travis-ci.org/aboucaud/pypher
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
