{ "info": { "author": "Ville Bergholm et al.", "author_email": "smite-meister@users.sourceforge.net", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: End Users/Desktop", "Intended Audience :: Information Technology", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Topic :: Scientific/Engineering :: Physics" ], "description": "===========================\nQuantum Information Toolkit\n===========================\n\n\nIntroduction\n============\n\nQuantum Information Toolkit (QIT) is a free, open source\nPython 2.7 / Python 3 package for various quantum information and\ncomputing -related purposes, released under GNU GPL.\nIt is a sister project of the MATLAB Quantum Information Toolkit\nand has equivalent functionality. QIT requires the following\nPython libraries:\n\n* `NumPy `_ 1.7.1\n* `SciPy `_ 0.11.0\n* `matplotlib `_ 1.2\n\nFor interactive use the `IPython `_ interactive shell is recommended.\n\nThe latest version can be found on our website,\n\n http://qit.sourceforge.net/\n\nThe toolkit is installed by downloading it from the Python Package Index,\nor directly from the Git repository. For an interactive session, start\nIPython with ::\n\n ipython --pylab\n\nand then import the toolkit using ::\n\n from qit import *\n\nTo get an overview of the features and capabilities of the toolkit,\nrun examples.tour()\n\n\nLicense\n=======\n\nQIT is released under the GNU General Public License version 3.\nThis basically means that you can freely use, share and modify it as\nyou wish, as long as you give proper credit to the authors and do not\nchange the terms of the license. See LICENSE.txt for the details.\n\n\nDesign notes\n============\n\nThe main design goals for this toolkit are ease of use and\ncomprehensiveness. It is primarily meant to be used as a tool for\nhypothesis testing, small simulations, and learning, not for\ncomputationally demanding simulations. Hence optimal efficiency of the\nalgorithms used is not a number one priority.\nHowever, if you think an algorithm could be improved without\ncompromising accuracy or maintainability, please let the authors know\nor become a contributor yourself!\n\n\nContributing\n============\n\nQIT is an open source project and your contributions are welcome.\nTo keep the code readable and maintainable, we ask you to follow these\ncoding guidelines:\n\n* Fully document all the modules, classes and functions using docstrings\n (purpose, calling syntax, output, approximations used, assumptions made...).\n The docstrings may contain reStructuredText markup for math, citations etc.\n* Add relevant literature references to doc/refs.bib and cite them in the function\n or module docstring using sphinxcontrib-bibtex syntax.\n* Instead of using multiple similar functions, use a single function\n performing multiple related tasks, see e.g. :func:`qit.state.state.measure`.\n* Raise an exception on invalid input.\n* Use variables sparingly, give them descriptive (but short) names.\n* Use brief comments to explain the logic of your code.\n* When you add new functions also add testing scripts for validating\n your code. If you modify existing code, make sure you didn't break\n anything by checking that the testing scripts still run successfully.\n\n\nAuthors\n=======\n\n* Ville Bergholm 2008-2014\n* Jacob D. Biamonte 2008-2009\n* James D. 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