Metadata-Version: 2.0
Name: pymrt
Version: 0.0.2.4
Summary: Python Magnetic Resonace Tools
Home-page: https://bitbucket.org/norok2/pymrt
Author: Riccardo Metere
Author-email: rick@metere.it
License: GPLv3+
Keywords: quantitative,MRI,qMRI,MT,susceptibility,relaxometry,qMT,neurophysics,neurology,physics,imaging,data,analysis
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Environment :: X11 Applications
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: System Administrators
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Utilities
Classifier: Operating System :: POSIX
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Provides-Extra: blessed
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: sympy
Requires-Dist: nibabel
Requires-Dist: matplotlib
Requires-Dist: pyparsing
Requires-Dist: numeral
Requires-Dist: appdirs
Requires-Dist: seaborn
Requires-Dist: pywavelets
Requires-Dist: h5py
Requires-Dist: pytk
Requires-Dist: pillow
Provides-Extra: blessed
Requires-Dist: blessed; extra == 'blessed'

=======================================
PyMRT - Python Magnetic Resonance Tools
=======================================

**PyMRT** - Python Magnetic Resonance Tools:
data analysis for quantitative MRI

.. code::

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Overview
--------
This software provides a support Python library and auxiliary console based
tools to perform common tasks for the analysis of quantitative MRI data.

It is relatively easy to extend and users are encouraged to tweak with it.

As a result of the code maturity, some of the library components may undergo
(eventually heavy) refactoring, although this is currently unexpected.


Releases information are available through ``NEWS.rst``.

For a more comprehensive list of changes see ``CHANGELOG.rst``.


Installation
------------
The recommended way of installing the software is through
`PyPI <https://pypi.python.org/pypi/pymrt>`_:

.. code:: shell

    $ pip install pymrt

Alternatively, you can clone the source repository from
`Bitbucket <https://bitbucket.org/norok2/pymrt>`_:

.. code:: shell

    $ mkdir pymrt
    $ cd pymrt
    $ git clone git@bitbucket.org:norok2/pymrt.git
    $ python setup.py install

For more details see also ``INSTALL.rst``.

License
-------
This work is licensed through the terms and conditions of the
`GPLv3+ <http://www.gnu.org/licenses/gpl-3.0.html>`_
The use of this software for scientific purpose leading to a publication
should be acknowledged through citation of the following reference:

**Metere, R., Möller, H.E., 2017. PyMRT and DCMPI: Two New Python Packages for MRI Data Analysis, #3816: Proceedings of the 25th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA.**


Acknowledgements
----------------
This software originated as part of my Ph.D. work at the
`Max Planck Institute for Human Cognitive and Brain Sciences
<http://www.cbs.mpg.de>`_ and the `University of Leipzig
<http://www.uni-leipzig.de>`_.

For a complete list of authors please see ``AUTHORS.rst``.

People who have influenced this work are acknowledged in ``THANKS.rst``.

This work was partly funded by the European Union
through the Seventh Framework Programme Marie Curie Actions
via the "Ultra-High Field Magnetic Resonance Imaging: HiMR"
Initial Training Network (FP7-PEOPLE-2012-ITN-316716).


