Aging_MouthReplace / dlibs /dlib /general_hash /random_hashing_abstract.h
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// Copyright (C) 2012 Davis E. King ([email protected])
// 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_