dlib C++ Library - random_hashing_abstract.h

    // Copyright (C) 2012  Davis E. King (davis@dlib.net)
    // License: Boost Software License   See LICENSE.txt for the full license.
    #undef DLIB_RANDOM_HAsHING_ABSTRACT_Hh_
    #ifdef DLIB_RANDOM_HAsHING_ABSTRACT_Hh_

    #include "random_hashing_abstract.h"
    #include "murmur_hash3.h"

    namespace dlib
    {

    // ----------------------------------------------------------------------------------------

        double uniform_random_hash (
            const uint64& k1,
            const uint64& k2,
            const uint64& k3
        );
        /*!
            ensures
                - This function uses hashing to generate uniform random values in the range [0,1).
                - To define this function precisely, assume we have an arbitrary sequence of
                  input triplets.  Then calling uniform_random_hash() on each of them should
                  result in a sequence of double values that look like numbers sampled
                  independently and uniformly at random from the interval [0,1).  This is true
                  even if there is some simple pattern in the inputs.  For example, (0,0,0),
                  (1,0,0), (2,0,0), (3,0,0), etc.
                - This function is deterministic.  That is, the same output is always returned
                  when given the same input.
        !*/

    // ----------------------------------------------------------------------------------------

        double gaussian_random_hash (
            const uint64& k1,
            const uint64& k2,
            const uint64& k3
        );
        /*!
            ensures
                - This function uses hashing to generate Gaussian distributed random values
                  with mean 0 and variance 1.
                - To define this function precisely, assume we have an arbitrary sequence of
                  input triplets.  Then calling gaussian_random_hash() on each of them should
                  result in a sequence of double values that look like numbers sampled
                  independently from a standard normal distribution.  This is true even if
                  there is some simple pattern in the inputs.  For example, (0,0,0), (1,0,0),
                  (2,0,0), (3,0,0), etc.
                - This function is deterministic.  That is, the same output is always returned
                  when given the same input.
        !*/

    // ----------------------------------------------------------------------------------------

    }

    #endif // DLIB_RANDOM_HAsHING_ABSTRACT_Hh_