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        "author": "Jonathan Marini",
        "author_email": "jonathan.r.marini@gmail.com",
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            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering"
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        "description": "NanoScope AFM\n==============\n\n.. image:: https://travis-ci.org/jmarini/nanoscope.svg?branch=master\n        :target: https://travis-ci.org/jmarini/nanoscope\n\n.. image:: https://coveralls.io/repos/jmarini/nanoscope/badge.svg\n        :target: https://coveralls.io/r/jmarini/nanoscope\n\nNanoscope is a library to handle parsing and processing of Veeco Nanoscope Dimension AFM files. Currently hard-coded to only work for version 0x05120130 and 0x09300201 since that is what I have access to for testing, but it will likely work on newer versions.\n\n\nFeatures\n--------\n\nThe current featureset includes:\n\n* Read raw Nanoscope files and image data (height, amplitude, phase, etc.)\n* Calculate standard summary information (RMS Roughness, Z-range, etc.)\n* Output the image in a Pillow-compatible format for saving\n* Data is cached after individual process steps to avoid unneeded reprocessing\n\n\nInstallation\n------------\n\nNanoscope can be easily installed using pip.\n\n.. code::\n\n    $ pip install nanoscope\n\n\nUsage\n-----\n\nAn example of typical usage is shown below, including using Pillow to save the image to png and printing Z-range and RMS data to the console\n\n.. code:: python\n\n    import nanoscope\n    from PIL import Image\n\n    p = nanoscope.read('./file.000')\n    p.height.process()\n    print(p.height.zrange, p.height.rms)\n    pixels = p.height.colorize()\n    Image.fromarray(pixels).save('file.png')\n\nArbitrary image types may also be accessed by name (case sensitive) and the name of all image types may be queried\n\n.. code::python\n\n    import nanoscope\n\n    p = nanoscope.read('./file.000')\n    p.image('ZSensor').process()\n\n    print(p.image_types())  # List of keys for each image type\n    print(p.describe_images())  # List of tuples (key, info) for each image type\n\n\nThe various image types can also be looped through using an iterator when processing, and the settings of the processing steps customized\n\n.. code:: python\n\n    import nanoscope\n\n    p = nanoscope.read('./file.000')\n    for img in p:\n        img.process(order=2)  # flatten the image using second-order function\n        print(img.type, img.rms)\n\n\nThe processing steps can also be called individually if needed\n\n.. code:: python\n\n    import nanoscope\n    p = nanoscope.read('./file.000')\n    p.height.flatten()  # flatten the image, defaults to first-order flatten\n    p.height.convert()  # convert the raw data to scaled values\n",
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