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Cleans up DESCRIPTION.txt
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hatesmeetings committed Feb 14, 2018
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10 changes: 4 additions & 6 deletions DESCRIPTION.txt
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A lightweight Python library that enables ordinal hashing of multidimensonal data via [Morton coding / Z-ordering](https://en.wikipedia.org/wiki/Z-order_curve), along with support for geospatial indexing.
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In mathematical analysis and computer science, *Z-order*, *Morton-order*, or a *Morton-code* is a function which maps multidimensional data to one dimension while preserving locality of the data points. It was introduced in 1966 by IBM researcher, *[G. M. Morton](https://domino.research.ibm.com/library/cyberdig.nsf/papers/0DABF9473B9C86D48525779800566A39/$File/Morton1966.pdf)*. *The z-value* of a point in multidimensions is calculated by interleaving the binary representations of its coordinate values. Once the data are sorted into this ordering, any one-dimensional data structure can be used, such as binary search trees, B-trees, skip lists, or hash tables. The resulting ordering can equivalently be described as the order one would achieve from a depth-first traversal of a quadtree,
where `{x, y, ..., K}` are combined into a single ordinal value that is easily compared, searched, and indexed against other *Morton numbers*.
A lightweight Python library that enables ordinal hashing of multidimensonal data via Morton coding / Z-ordering, along with support for geospatial indexing.

In mathematical analysis and computer science, `Z-order`, `Morton-order`, or a `Morton-code` is a function which maps multidimensional data to one dimension while preserving locality of the data points. It was introduced in 1966 by IBM researcher, G. M. Morton. The z-value of a point in multidimensions is calculated by interleaving the binary representations of its coordinate values. Once the data are sorted into this ordering, any one-dimensional data structure can be used, such as binary search trees, B-trees, skip lists, or hash tables. The resulting ordering can equivalently be described as the order one would achieve from a depth-first traversal of a quadtree,
where `{x, y, ..., K}` are combined into a single ordinal value that is easily compared, searched, and indexed against other Morton numbers.
2 changes: 1 addition & 1 deletion setup.py
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def build():
setup(
name='pymorton',
version='1.0.0',
version='1.0.1',
author='Trevor Prater',
author_email='[email protected]',
description='A lightweight morton coder with lat/long support.',
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