问题
I'm trying to convert this line of matlab in C++: rp = randperm(p);
Following the randperm
documentation:
randperm uses the same random number generator as rand
And in rand
page:
rand returns a single uniformly distributed random number
So rand
follows an uniform distribution. My C++ code is based on:
std::random_device rd;
std::mt19937 g(rd());
std::shuffle(... , ... ,g);
My question is: the code above follows an uniform distribution? If not, how to do so?
回答1:
The different classes from the C++ random number library roughly work as follows:
- std::random_device is a uniformly-distributed random number generator that may access a hardware device in your system, or something like
/dev/random
on Linux. It is usually just used to seed a pseudo-random generator, since the underlying device wil usually run out of entropy quickly. - std::mt19937 is a fast pseudo-random number generator using the Mersenne Twister engine which, according to the original authors' paper title, is also uniform. This generates fully random 32-bit or 64-bit unsigned integers. Since
std::random_device
is only used to seed this generator, it does not have to be uniform itself (e.g., you often seed the generator using a current time stamp, which is definitely not uniformly distributed). - Typically, you use a generator such as
std::mt19937
to feed a particular distribution, e.g. a std::uniform_int_distribution or std::normal_distribution which then take the desired distribution shape. - std::shuffle, according to the documentation,
Reorders the elements in the given range
[first, last)
such that each possible permutation of those elements has equal probability of appearance.
In your code example, you use the std::mt19937
PRNG to feed std::shuffle
. So, std::mt19937
is uniform, and std::shuffle
should also behave uniformly. So, everything is as uniform as it can be.
来源:https://stackoverflow.com/questions/38367976/do-stdrandom-device-and-stdmt19937-follow-an-uniform-distribution