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68 lines
3.4 KiB
Plaintext
68 lines
3.4 KiB
Plaintext
[/
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Copyright 2011 - 2020 John Maddock.
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Copyright 2013 - 2019 Paul A. Bristow.
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Copyright 2013 Christopher Kormanyos.
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Distributed under the Boost Software License, Version 1.0.
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(See accompanying file LICENSE_1_0.txt or copy at
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http://www.boost.org/LICENSE_1_0.txt).
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]
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[section:random Generating Random Numbers]
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Random numbers are generated in conjunction with Boost.Random.
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There is a single generator that supports generating random integers with large bit counts:
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[@http://www.boost.org/doc/html/boost/random/independent_bits_engine.html `independent_bits_engine`].
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This type can be used with either ['unbounded] integer types, or with ['bounded] (i.e. fixed precision) unsigned integers:
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[random_eg1]
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Program output is:
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[random_eg1_out]
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In addition, the generator adaptors [@http://www.boost.org/doc/html/boost/random/discard_block_engine.html `discard_block`],
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[@http://www.boost.org/doc/html/boost/random/xor_combine_engine.html `xor_combine_engine`] and
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[@http://www.boost.org/doc/html/boost/random/discrete_distribution.html `discrete_distribution`] can be used
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with multiprecision types. Note that if you seed an `independent_bits_engine`, then you are actually seeding
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the underlying generator, and should therefore provide a sequence of unsigned 32-bit values as the seed.
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Alternatively we can generate integers in a given range using
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[@http://www.boost.org/doc/html/boost/random/uniform_int_distribution.html `uniform_int_distribution`], this will
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invoke the underlying engine multiple times to build up the required number of bits in the result:
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[random_eg2]
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[random_eg2_out]
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It is also possible to use [@http://www.boost.org/doc/html/boost/random/uniform_int_distribution.html `uniform_int_distribution`]
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with a multiprecision generator such as [@http://www.boost.org/doc/html/boost/random/independent_bits_engine.html `independent_bits_engine`].
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Or to use [@http://www.boost.org/doc/html/boost/random/uniform_smallint.html `uniform_smallint`] or
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[@http://www.boost.org/doc/html/boost/random/random_number_generator.html `random_number_generator`] with multiprecision types.
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Floating-point values in \[0,1) are most easily generated using [@http://www.boost.org/doc/html/boost/random/generate_canonical.html `generate_canonical`],
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note that `generate_canonical` will call the generator multiple times to produce the requested number of bits, for example we can use
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it with a regular generator like so:
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[random_eg3]
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[random_eg3_out]
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Note however, the distributions do not invoke the generator multiple times to fill up the mantissa of a multiprecision floating-point type
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with random bits. For these therefore, we should probably use a multiprecision generator (i.e. `independent_bits_engine`) in combination
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with the distribution:
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[random_eg4]
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[random_eg4_out]
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And finally, it is possible to use the floating-point generators [@http://www.boost.org/doc/html/boost/random/lagged_fibonacci_01_engine.html `lagged_fibonacci_01_engine`]
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and [@http://www.boost.org/doc/html/boost/random/subtract_with_idp144360752.html `subtract_with_carry_01_engine`] directly with multiprecision floating-point types.
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It's worth noting, however, that there is a distinct lack of literature on generating high bit-count random numbers, and therefore a lack of "known good" parameters to
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use with these generators in this situation. For this reason, these should probably be used for research purposes only:
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[random_eg5]
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[endsect] [/section:random Generating Random Numbers]
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