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Metadata-Version: 2.4
Name: mrcz
Version: 0.5.9
Summary: MRCZ meta-compressed image file-format library
Author-email: "Robert A. McLeod" <robbmcleod@gmail.com>
License-Expression: BSD-3-Clause
Requires-Python: >=3.11
Description-Content-Type: text/x-rst
License-File: LICENSE.txt
License-File: AUTHORS.txt
Requires-Dist: numpy
Dynamic: license-file
==============================================
Python MRCZ meta-compressed file-format module
==============================================
``mrcz`` is a package designed to supplement the venerable MRC image file
format with a highly efficient compressed variant, using the ``blosc``
meta-compressor library to shrink files on disk and greatly accelerate file
input/output for the era of "Big Data" in electron and optical microscopy.
Python versions 2.7, 3.4-3.6 are supported.
``mrcz`` is currently considered to be a `beta` development state.
``mrcz`` is released under the BSD 3-clause license.
Installation
------------
A scientific Python installation (such as Anaconda, WinPython, or Canopy) is
advised. After installation of your Python environment, from a command prompt
type::
pip install mrcz
``mrcz`` has the following dependencies:
* ``numpy``
* ``blosc`` (optionally, but highly recommended)
Feature List
------------
* Import: DM4, MRC, MRCZ formats
* Export: MRC, MRCZ formats
* Compress and bit-shuffle image stacks and volumes with ``blosc`` meta-compressor
* Asynchronous read and write operations.
* Support in the ``hyperspy`` electron microscopy package.
Documentation
-------------
Documentation is hosted at http://python-mrcz.readthedocs.io/
Authors
-------
See ``AUTHORS.txt``.
Citations
---------
* R.A. McLeod, R. Diogo-Righetto, A. Stewart, H. Stahlberg, "MRCZ – A file
format for cryo-TEM data with fast compression," Journal of Structural Biology,
201 (3) (March 2018): 252-267, https://doi.org/10.1016/j.jsb.2017.11.012
* A. Cheng et al., "MRC2014: Extensions to the MRC format header for electron
cryo-microscopy and tomography", Journal of Structural Biology 192(2): 146-150,
November 2015, http://dx.doi.org/10.1016/j.jsb.2015.04.002
* V. Haenel, "Bloscpack: a compressed lightweight serialization format for
numerical data", arXiv:1404.6383
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