/usr/include/viennacl/tools/random.hpp is in libviennacl-dev 1.7.1+dfsg1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | #ifndef VIENNACL_TOOLS_RANDOM_HPP
#define VIENNACL_TOOLS_RANDOM_HPP
/* =========================================================================
Copyright (c) 2010-2016, Institute for Microelectronics,
Institute for Analysis and Scientific Computing,
TU Wien.
Portions of this software are copyright by UChicago Argonne, LLC.
-----------------
ViennaCL - The Vienna Computing Library
-----------------
Project Head: Karl Rupp rupp@iue.tuwien.ac.at
(A list of authors and contributors can be found in the manual)
License: MIT (X11), see file LICENSE in the base directory
============================================================================= */
#include <ctime>
#include <cstdlib>
#include <cmath>
/** @file viennacl/tools/random.hpp
* @brief A small collection of sequential random number generators.
*
* Should not be considered a source of high-quality random numbers.
* It is, however, enough to produce meaningful initial guesses.
*/
namespace viennacl
{
namespace tools
{
/** @brief Random number generator for returning uniformly distributed values in the closed interval [0, 1]
*
* Currently based on rand(), which may have fairly poor quality.
* To be replaced in the future, but serves the purpose for the time being.
*/
template<typename NumericT>
class uniform_random_numbers
{
public:
NumericT operator()() const { return static_cast<NumericT>(double(rand()) / double(RAND_MAX)); }
};
/** @brief Random number generator for returning normally distributed values
*
* Implementation based on Box-Muller transformation:
* https://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform
*/
template<typename NumericT>
class normal_random_numbers
{
public:
normal_random_numbers(NumericT mean = NumericT(0), NumericT sigma = NumericT(1)) : mean_(mean), sigma_(sigma) {}
NumericT operator()() const
{
NumericT u = 0;
while (std::fabs(u) <= 0 || u >= NumericT(1))
u = static_cast<NumericT>(double(rand()) / double(RAND_MAX));
NumericT v = 0;
while (std::fabs(v) <= 0 || v >= NumericT(1))
v = static_cast<NumericT>(double(rand()) / double(RAND_MAX));
return mean_ + sigma_ * std::sqrt(NumericT(-2) * std::log(u)) * std::cos(NumericT(6.28318530717958647692) * v);
}
private:
NumericT mean_;
NumericT sigma_;
};
}
}
#endif
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