Metadata-Version: 1.0
Name: NearPy
Version: 0.1
Summary: Framework for fast approximated nearest neighbour search.
Home-page: http://pypi.python.org/pypi/NearPy/
Author: Ole Krause-Sparmann
Author-email: ole@pixelogik.de
License: LICENSE.txt
Description: ===========
        NearPy
        ===========
        
        NearPy is a Python framework for fast (approximated) nearest neighbour search in high dimensional vector spaces using different locality-sensitive hashing methods.
        
        It allows to experiment and to evaluate new methods but is also production-ready. It comes with a redis storage adapter.
        
        Example usage:
        
            from nearpy import Engine
            from nearpy.hashes import RandomBinaryProjections
        
            # Dimension of our vector space
            dimension = 500
        
            # Create a random binary hash with 10 bits
            rbp = RandomBinaryProjections('rbp', 10)
        
            # Create engine with pipeline configuration
            engine = Engine(dimension, lshashes=[rbp])
        
            # Index 1000000 random vectors (set their data to a unique string)
            for index in range(100000):
                v = numpy.random.randn(dimension)
                engine.store_vector(v, 'data_%d' % index)
        
            # Create random query vector
            query = numpy.random.randn(dimension)
        
            # Get nearest neighbours
            N = engine.neighbours(query)
        
        Read more here: http://nearpy.io
        
Platform: UNKNOWN
