From: Matthias Troyer (troyer_at_[hidden])
Date: 2006-03-18 09:14:44
On Mar 18, 2006, at 8:54 AM, John Maddock wrote:
>> This seems to be dependant on the type of generator you use. Try
>> lagged_fibonacci. The casting and dividing involved in uniform_real
>> appears to loose a lot of accuracy, but lagged_fibonacci generates
>> doubles between 0 and 1, so there's no cast and it's dividing by 1.
> Just a quick update for those who are interested: using
> does indeed solve the problem and allows the iostreams code I
> posted earlier
> to detect the VC8 streaming problem.
> Unfortunately lagged_fibonacci isn't part of TR1: the only real number
> generator that is (subtract_with_carry_01) appears to still leave
> the final
> 4 bits as zero :-(
There are simple reason why lagged_fibonacci and the linear
congruential generators fill the low bits with apparently random
values, and the Mersenne twister does not.
- The Mersenne twister produces integers modulo 2^32. Hence if you
scale to a uniform real in the interval [0,1), the integer value is
divided by 2^32, and the low bits remain 0.
- With the 32-bit linear congruential generators, such as
minstd_rand, the numbers produced are modulo 2^31-1, a prime number,
and not modulo a power of 2. Hence, the low bits look random,
although you actually get fewer distinct floating point values (only
- The lagged Fibonacci floating point generators are by default
seeded with minstd_rand0, and hence have low bits that are nonzero.
If instead you were to seed it with numbers created from a Mersenne
twister, you would see the same problems.
Having said that I think that for most applications it is no problem
that the low 20 bits remain zero. I don't know of any application
requiring these low bits to be random as well. Usually 32 random bits
are more than enough. If, however, you need more bits than I would
recommend looking into 64 bit generators, such as the lcg64 in the
SPRNG library, a wrapper for which exists in the sandbox.
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