Metadata-Version: 2.1
Name: libertem
Version: 0.2.1
Summary: Open pixelated STEM framework
Home-page: https://libertem.github.io/LiberTEM/
Author: the LiberTEM team
Author-email: libertem-dev@googlegroups.com
License: GPL v3
Description: |gitter|_ |travis|_ |appveyor|_ |zenodo|_
        
        .. |gitter| image:: https://badges.gitter.im/Join%20Chat.svg
        .. _gitter: https://gitter.im/LiberTEM/Lobby
        
        .. |travis| image:: https://api.travis-ci.org/LiberTEM/LiberTEM.svg?branch=master
        .. _travis: https://travis-ci.org/LiberTEM/LiberTEM
        
        .. |appveyor| image:: https://ci.appveyor.com/api/projects/status/wokeo6ee2frq481m/branch/master?svg=true
        .. _appveyor: https://ci.appveyor.com/project/sk1p/libertem
        
        .. |zenodo| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1478763.svg
        .. _zenodo: https://doi.org/10.5281/zenodo.1478763
        
        
        
        LiberTEM is an open source platform for high-throughput distributed processing of large-scale binary data sets using a simplified `MapReduce programming model <https://en.wikipedia.org/wiki/MapReduce>`_. The current focus is `pixelated <https://en.wikipedia.org/wiki/Scanning_transmission_electron_microscopy#Universal_detectors>`_ scanning transmission electron microscopy (`STEM <https://en.wikipedia.org/wiki/Scanning_transmission_electron_microscopy>`_)  and scanning electron beam diffraction data.
        
        It is `designed for high throughput and scalability <https://libertem.github.io/LiberTEM/architecture.html>`_ on PCs, single server nodes, clusters and cloud services. On clusters it can use fast distributed
        local storage on high-performance SSDs. That way it achieves `very high aggregate IO performance <https://libertem.github.io/LiberTEM/performance.html>`_ on a compact and cost-efficient system built from stock components.
        
        LiberTEM is supported on Linux, Mac OS X and Windows. Other platforms
        that allow installation of Python 3 and the required packages will likely work as well. The GUI is running
        in a web browser.
        
        Installation
        ------------
        
        The short version:
        
        .. code-block:: shell
        
            $ virtualenv -p python3.6 ~/libertem-venv/
            $ source ~/libertem-venv/bin/activate
            (libertem) $ pip install libertem[torch]
        
        Please see `our documentation <https://libertem.github.io/LiberTEM/install.html>`_ for details!
        
        Deployment as a single-node system for a local user is thoroughly tested and can be considered stable. Deployment on a cluster is 
        experimental and still requires some additional work, see `Issue #105 <https://github.com/LiberTEM/LiberTEM/issues/105>`_.
        
        Applications
        ------------
        
        - Virtual detectors (virtual bright field, virtual HAADF, center of mass ,
          custom shapes via masks)
        - `Analysis of amorphous materials <https://libertem.github.io/LiberTEM/app/amorphous.html>`_
        - `Strain mapping <https://libertem.github.io/LiberTEM/app/strain.html>`_
        - `Custom analysis functions (user-defined functions) <https://libertem.github.io/LiberTEM/udf.html>`_
        
        Please see `the applications section <https://libertem.github.io/LiberTEM/applications.html>`_ of our documentation for details!
        
        The Python API and user-defined functions (UDFs) can be used for more complex operations with arbitrary masks and other features like data export. There are example Jupyter notebooks available in the `examples directory <https://github.com/LiberTEM/LiberTEM/tree/master/examples>`_.
        If you are having trouble running the examples, please let us know, either by filing an issue
        or by `joining our Gitter chat <https://gitter.im/LiberTEM/Lobby>`_.
        
        LiberTEM is suitable as a high-performance processing backend for other applications, including live data streams. `Contact us <https://gitter.im/LiberTEM/Lobby>`_ if you are interested! 
        
        
        LiberTEM is evolving rapidly and prioritizes features following user demand and contributions. In the future we'd like to implement live acquisition, and more analysis methods for all applications of pixelated STEM and other large-scale detector data.
        If you like to influence the direction this
        project is taking, or if you'd like to `contribute <https://libertem.github.io/LiberTEM/contributing.html>`_, please join our `gitter chat <https://gitter.im/LiberTEM/Lobby>`_
        and our `general mailing list <https://groups.google.com/forum/#!forum/libertem>`_. 
        
        File formats
        ------------
        
        LiberTEM currently opens most file formats used for pixelated STEM. See `our general information on loading data <https://libertem.github.io/LiberTEM/formats.html>`_
        and `format-specific documentation <https://libertem.github.io/LiberTEM/reference/dataset.html#formats>`_ for more information!
        
        - Raw binary files
        - Thermo Fisher EMPAD detector  files
        - `Quantum Detectors MIB format <http://quantumdetectors.com/wp-content/uploads/2017/01/1532-Merlin-for-EM-Technical-Datasheet-v2.pdf>`_
        - Nanomegas .blo block files
        - `Gatan K2 IS <https://web.archive.org/web/20180809021832/http://www.gatan.com/products/tem-imaging-spectroscopy/k2-camera>`_ raw format
        - Gatan DM3 and DM4: See `Issue #291 <https://github.com/LiberTEM/LiberTEM/issues/291>`_ Please contact us if you would like to process such data!
        - FRMS6 from PNDetector pnCCD cameras  (currently alpha, gain correction still needs UI changes)
        - FEI SER files (via `openNCEM <https://github.com/ercius/openNCEM>`_)
        - HDF5-based formats such as Hyperspy files, NeXus and EMD
        - Please contact us if you are interested in support for an additional format!
        
        License
        -------
        
        LiberTEM is licensed under GPLv3. The I/O parts are also available under the MIT license, please see LICENSE files in the subdirectories for details.
        
Keywords: electron microscopy
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Environment :: Web Environment
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: JavaScript
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Provides-Extra: hdfs
Provides-Extra: hdbscan
Provides-Extra: torch
Provides-Extra: pyfftw
