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        "author": "Jeremie DECOCK",
        "author_email": "jd.jdhp@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Application Frameworks",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": ".. image:: https://travis-ci.org/jeremiedecock/pywi.svg?branch=master\n    :target: https://travis-ci.org/jeremiedecock/pywi\n\n=============================\nPyWI - Python Wavelet Imaging\n=============================\n\nCopyright (c) 2016-2018 Jeremie DECOCK (www.jdhp.org)\n\n* Web site: http://www.pywi.org/\n* Online documentation: http://www.pywi.org/docs/\n* Examples: http://www.pywi.org/docs/gallery/\n* Notebooks: https://github.com/jeremiedecock/pywi-notebooks\n* Source code: https://github.com/jeremiedecock/pywi\n* Issue tracker: https://github.com/jeremiedecock/pywi/issues\n* PyWI on PyPI: https://pypi.org/project/pywi/\n* PyWI on Anaconda Cloud: https://anaconda.org/jdhp/pywi\n\n.. Former documentation (readthedocs): http://sap-cta-data-pipeline.readthedocs.io/en/latest/\n.. Former documentation (github pages): https://jeremiedecock.github.io/pywi/\n\nDescription\n===========\n\nPyWI is a Python image filtering library aimed at removing additive background noise\nfrom raster graphics images.\n\n* Input: an image file containing the raster graphics to clean (i.e. an image\n  defined as a classic rectangular lattice of square pixels).\n* Output: an image file containing the cleaned raster graphics.\n\nThe image filter relies on multiresolution analysis methods (Wavelet\ntransforms) that remove some scales (frequencies) locally in space. These\nmethods are particularly efficient when signal and noise are located at\ndifferent scales (or frequencies). Optional features improve the SNR ratio when\nthe (clean) signal constitute a single cluster of pixels on the image (e.g.\nelectromagnetic showers produced with Imaging Atmospheric Cherenkov\nTelescopes). This library is written in Python and is based on the existing\nCosmostat tools iSAp (Interactive Sparse Astronomical data analysis Packages\nhttp://www.cosmostat.org/software/isap/).\n\nThe PyWI library also contains a dedicated package to optimize the image filter\nparameters for a given set of images (i.e. to adapt the filter to a specific\nproblem). From a given training set of images (containing pairs of noised and\nclean images) and a given performance estimator (a function that assess the\nimage filter parameters comparing the cleaned image to the actual clean image),\nthe optimizer can determine the optimal filtering level for each scale.\n\n.. warning::\n\n    This project is in beta stage.\n\nFeatures\n========\n\nThe PyWI library contains:\n\n* wavelet transform and wavelet filtering functions for image multiresolution\n  analysis and filtering;\n* additional filter to remove some image components (non-significant pixels\n  clusters);\n* a set of generic filtering performance estimators (MSE, NRMSE, SSIM, PSNR,\n  image moment's difference), some relying on the scikit-image Python library\n  (supplementary estimators can be easily added to meet particular needs);\n* a graphical user interface to visualize the filtering process in the wavelet\n  transformed space;\n* an Evolution Strategies (ES) algorithm known in the mathematical optimization\n  community for its good convergence rate on generic derivative-free continuous\n  global optimization problems (Beyer, H. G. (2013) \"The theory of evolution\n  strategies\", Springer Science & Business Media);\n* additional tools to manage and monitor the parameter optimization.\n\nDependencies\n============\n\n.. Highly inspired by http://docs.astropy.org/en/stable/_sources/install.rst.txt\n\nPyWI has the following strict requirements:\n\n* `Python <https://www.python.org/>`_ 3.5 or 3.6\n* `Numpy <http://www.numpy.org/>`_\n\nPyWI also depends on other packages for optional features:\n\n* `Scipy <https://www.scipy.org/>`_\n* `Scikit-image <http://scikit-image.org/>`_\n* `Pillow (a.k.a. PIL) <https://pillow.readthedocs.io/en/latest/>`_ to read and write many image formats (PNG, JPEG, TIFF, ...)\n* `Astropy <http://www.astropy.org/>`_ to provide Fits file format\n* `Pandas <http://pandas.pydata.org/>`_\n* `Matplotlib <http://matplotlib.org/>`_ 1.5 or later to provide plotting functionality\n* `Cosmostat iSAP Sparce2D <http://www.cosmostat.org/software/isap/>`_\n\nHowever, note that these only need to be installed if those particular features\nare needed. PyWI will import even if these dependencies are not installed.\n\n.. _install:\n\nInstallation\n============\n\nUsing pip\n---------\n\nMost major projects upload official packages to the *Python Package Index*.\nThey can be installed on most operating systems using Python standard `pip`\npackage manager.\n\nNote that you need to have `Python3.x` and `pip` already installed on your system.\n\n.. warning::\n\n    Users of the Anaconda python distribution should follow the instructions\n    for Anaconda install (see `Using conda`_ bellow).\n\n.. note::\n\n    You will need a C compiler (e.g. ``gcc`` or ``clang``) to be installed to\n    install some dependencies (e.g. Numpy).\n\n.. note::\n\n    The ``--no-deps`` flag is optional, but highly recommended if you already\n    have Numpy installed, since otherwise pip will sometimes try to \"help\" you\n    by upgrading your Numpy installation, which may not always be desired.\n\n.. note::\n\n    If you get a ``PermissionError`` this means that you do not have the\n    required administrative access to install new packages to your Python\n    installation.  In this case you may consider using the ``--user`` option\n    to install the package into your home directory. You can read more\n    about how to do this in the `pip documentation\n    <https://pip.pypa.io/en/stable/user_guide/#user-installs>`_.\n\n    Alternatively, if you intend to do development on other software that uses\n    PyWI, such as an affiliated package, consider installing PyWI into a\n    `virtualenv <http://docs.astropy.org/en/stable/development/workflow/virtualenv_detail.html#using-virtualenv>`_.\n\n    Do **not** install PyWI or other third-party packages using ``sudo``\n    unless you are fully aware of the risks.\n\nOn MacOSX and Gnu/Linux\n~~~~~~~~~~~~~~~~~~~~~~~\n\nYou can install PyWI using the following command (in a terminal)::\n\n    pip install pywi --no-deps\n\n.. python -m pip install --user numpy scipy matplotlib pandas\n\n.. It is recommended to use the --user flag to ``pip`` (note: do not use sudo pip,\n.. which can cause problems) to install packages in your local user space instead\n.. of the shared system directories.\n.. TODO: the --user flag has an issue (bug?): console scripts (pywi-mrfilter, ...)\n.. are not directly (i.e. without updating the PATH variable) available anymore (at\n.. least on MacOSX/Anaconda).\n\nAs an alternative, you can install PyWI from the downloaded source code::\n\n    python3 setup.py install --no-deps\n\n.. There's also a package for Debian/Ubuntu::\n.. \n..     sudo apt-get install pywi\n\nIf PyWI is already installed on your system you can upgrade it with this command::\n\n    pip install --upgrade pywi\n\nTo uninstall PyWI, type::\n\n    pip uninstall pywi\n\nOn Windows\n~~~~~~~~~~\n\n.. Note:\n.. \n..     The following installation procedure has been tested to work with Python\n..     3.4 under Windows 7.\n..     It should also work with recent Windows systems.\n\nYou can install PyWI using the following command (in a `command prompt`_)::\n\n    py -m pip install pywi --no-deps\n\n.. It is recommended to use the --user flag to ``pip`` (note: do not use sudo pip,\n.. which can cause problems) to install packages in your local user space instead\n.. of the shared system directories.\n.. TODO: the --user flag has an issue (bug?): console scripts (pywi-mrfilter, ...)\n.. are not directly (i.e. without updating the PATH variable) available anymore (at\n.. least on MacOSX/Anaconda).\n\nAs an alternative, you can install PyWI from the downloaded source code::\n\n    py setup.py install --no-deps\n\nIf PyWI is already installed on your system you can upgrade it with this command::\n\n    py -m pip install --upgrade pywi\n\nTo uninstall PyWI, type::\n\n    py -m uninstall pywi\n\n\n.. _anaconda_install:\n\nUsing conda\n-----------\n\nTo install this package with conda run in a terminal::\n\n    conda install -c jdhp pywi\n\nSo far, the PyWI Anaconda package is only available for MacOSX.\nA package for Linux and Windows will be available soon.\n\n.. note::\n\n    Attempting to use `pip <https://pip.pypa.io>`__ to upgrade your installation of PyWI may result\n    in a corrupted installation.\n\nCosmostat iSAP Sparce2D installation\n====================================\n\n1. Download http://www.cosmostat.org/wp-content/uploads/2014/12/ISAP_V3.1.tgz (see http://www.cosmostat.org/software/isap/)\n2. Unzip this archive, go to the \"sparse2d\" directory and compile the sparse2d\n   library. It should generate two executables named ``mr_transform`` and ``mr_filter``::\n\n    tar -xzvf ISAP_V3.1.tgz\n    cd ISAP_V3.1/cxx\n    tar -xzvf sparse2d_V1.1.tgz\n    cd sparse2d\n    compile the content of this directory\n\nAn automated compilation and installation script for Linux is available\n`there <https://github.com/tino-michael/tino_cta/blob/master/grid/compile_mrfilter_pilot.sh>`_\n(author: `Tino Michael <https://github.com/tino-michael>`_).\n\n.. Also available in `utils/compile_isap_sparce2d.sh`\n\nExample\n=======\n\n1. Download a sample image (e.g. `archives_ngc3576.png <https://gist.githubusercontent.com/jeremiedecock/144c83f74e46b171ab3a426230d40848/raw/4a9ea99dd18504baff404a074a4e7541d98a50c5/archives_ngc3576.png>`_)\n2. In your system terminal, from the directory that contains the sample image, type::\n  \n    pywi-mrtransform -t 256,256,256,0 --plot archives_ngc3576.png\n    pywi-mrfilter -s 256,256,256,0 --plot archives_ngc3576.png\n\n3. Type ``pywi-mrtransform -h`` or ``pywi-mrfilter -h`` to display the list of\n   available options and their documentation.\n\n.. 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