Metadata-Version: 1.1
Name: pywi
Version: 0.1.dev8
Summary: Python Wavelet Imaging
Home-page: https://github.com/jeremiedecock/pywi
Author: Jeremie DECOCK
Author-email: jd.jdhp@gmail.com
License: UNKNOWN
Download-URL: https://github.com/jeremiedecock/pywi
Description-Content-Type: UNKNOWN
Description: =============================
        PyWI - Python Wavelet Imaging
        =============================
        
        Copyright (c) 2016-2018 Jeremie DECOCK (www.jdhp.org)
        
        * Online documentation: https://jeremiedecock.github.io/pywi/
        * Source code: https://github.com/jeremiedecock/pywi
        * Issue tracker: https://github.com/jeremiedecock/pywi/issues
        * PyWI on PyPI: https://pypi.org/project/pywi/
        
        .. Former documentation: http://sap-cta-data-pipeline.readthedocs.io/en/latest/
        
        Description
        ===========
        
        PyWI is an image filtering library aimed at removing additive background noise
        from raster graphics images.
        
        * Input: a FITS file containing the raster graphics to clean (i.e. an image
          defined as a classic rectangular lattice of square pixels).
        * Output: a FITS file containing the cleaned raster graphics.
        
        The image filter relies on multiresolution analysis methods (Wavelet
        transforms) that remove some scales (frequencies) locally in space. These
        methods are particularly efficient when signal and noise are located at
        different scales (or frequencies). Optional features improve the SNR ratio when
        the (clean) signal constitute a single cluster of pixels on the image (e.g.
        electromagnetic showers produced with Imaging Atmospheric Cherenkov
        Telescopes). This library is written in Python and is based on the existing
        Cosmostat tools iSAp (Interactive Sparse Astronomical data analysis Packages
        http://www.cosmostat.org/software/isap/).
        
        The PyWI library also contains a dedicated package to optimize the image filter
        parameters for a given set of images (i.e. to adapt the filter to a specific
        problem). From a given training set of images (containing pairs of noised and
        clean images) and a given performance estimator (a function that assess the
        image filter parameters comparing the cleaned image to the actual clean image),
        the optimizer can determine the optimal filtering level for each scale.
        
        The PyWI library contains:
        
        * wavelet transform and wavelet filtering functions for image multiresolution
          analysis and filtering;
        * additional filter to remove some image components (non-significant pixels
          clusters);
        * a set of generic filtering performance estimators (MSE, NRMSE, SSIM, PSNR,
          image moment's difference), some relying on the scikit-image Python library
          (supplementary estimators can be easily added to meet particular needs);
        * a graphical user interface to visualize the filtering process in the wavelet
          transformed space;
        * an Evolution Strategies (ES) algorithm known in the mathematical optimization
          community for its good convergence rate on generic derivative-free continuous
          global optimization problems (Beyer, H. G. (2013) "The theory of evolution
          strategies", Springer Science & Business Media);
        * additional tools to manage and monitor the parameter optimization.
        
        Note:
        
            This project is in beta stage.
        
        
        Dependencies
        ============
        
        * Python >= 3.0
        * Numpy
        * Scipy
        * Scikit-image
        * _Cosmostat _iSAP Sparce2D
        
        .. _install:
        
        Installation
        ============
        
        Gnu/Linux
        ---------
        
        You can install, upgrade, uninstall PyWI with these commands (in a
        terminal)::
        
            pip install --pre pywi
            pip install --upgrade pywi
            pip uninstall pywi
        
        Or, if you have downloaded the PyWI source code::
        
            python3 setup.py install
        
        .. There's also a package for Debian/Ubuntu::
        .. 
        ..     sudo apt-get install pywi
        
        Windows
        -------
        
        .. Note:
        .. 
        ..     The following installation procedure has been tested to work with Python
        ..     3.4 under Windows 7.
        ..     It should also work with recent Windows systems.
        
        You can install, upgrade, uninstall PyWI with these commands (in a
        `command prompt`_)::
        
            py -m pip install --pre pywi
            py -m pip install --upgrade pywi
            py -m pip uninstall pywi
        
        Or, if you have downloaded the PyWI source code::
        
            py setup.py install
        
        MacOSX
        -------
        
        .. Note:
        .. 
        ..     The following installation procedure has been tested to work with Python
        ..     3.5 under MacOSX 10.9 (*Mavericks*).
        ..     It should also work with recent MacOSX systems.
        
        You can install, upgrade, uninstall PyWI with these commands (in a
        terminal)::
        
            pip install --pre pywi
            pip install --upgrade pywi
            pip uninstall pywi
        
        Or, if you have downloaded the PyWI source code::
        
            python3 setup.py install
        
        Cosmostat iSAP Sparce2D installation
        ====================================
        
        1. Download http://www.cosmostat.org/wp-content/uploads/2014/12/ISAP_V3.1.tgz (see http://www.cosmostat.org/software/isap/)
        2. Unzip this archive, go to the "sparse2d" directory and compile the sparse2d
           library. It should generate two executables named ``mr_transform`` and ``mr_filter``::
        
            tar -xzvf ISAP_V3.1.tgz
            cd ISAP_V3.1/cxx
            tar -xzvf sparse2d_V1.1.tgz
            cd sparse2d
            compile the content of this directory
        
        Example
        =======
        
        1. Download a sample image (`shower.fits <https://raw.githubusercontent.com/jdhp-misc/sample-images/master/shower.fits>`_)
        2. In your system terminal, type::
          
            pywi_mrfilter shower.fits
        
        3. Use the ``-h`` option for more options
        
        A "benchmark mode" can also be used to clean images and assess cleaning
        algorithms (it's still a bit experimental): use the additional option ``-b all``
        in each command (and put several fits files in input e.g. ``\*.fits``)
        
        Bug reports
        ===========
        
        To search for bugs or report them, please use the PyWI Bug Tracker at:
        
            https://github.com/jeremiedecock/pywi/issues
        
        
        .. _PyWI: https://github.com/jeremiedecock/pywi
        .. _command prompt: https://en.wikipedia.org/wiki/Cmd.exe
        .. _Cosmostat: http://www.cosmostat.org/
        .. _iSAP: http://www.cosmostat.org/software/isap
        
Keywords: multiresolution image filter wavelet
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
