I want to learn why my code is not working as I expect. I mean I want to generate a double number between 0 and 1 and I have learnt that when I use
(double)rand() / RAND_MAX, it works well. However I read that srand(time(NULL))
changes each generated random number every time I compile. However When I use them together the program generates same random number all the time. Why does this happen? Thanks.
Here is my code:
//srand(time(NULL));
number = (double)rand() / (double)RAND_MAX;
The srand() function initializes the pseudo-random number generator. You can think of that like it is pointing to the rand() a number to start its 'calculations'. Every time you compile and run your program the srand() function gives your rand() function the seed of time(NULL) (which by the way is a very big number changing every second). If you don't use the srand(), your rand() will always return the same sequence of numbers because it is given by default a standart non-changing seed (number to start the 'calculations'). You can try to give your srand() a static parameter like: srand(1500) You will see that it will return different numbers but their sequence will again be the same every time u compile and run.
For more info read here:
http://www.cplusplus.com/reference/cstdlib/srand/
http://www.cplusplus.com/reference/cstdlib/rand/
Related
I was playing around with the lua interpretor and made this little program that generates two numbers and compares them. The program runs until the numbers match. The first number is randomly generated using math.random(), and is set to 1, and 100000. The second value that is generated to compare is between 1 and 100. It also keeps track of how many times the program loops. The program works as intended, but something strange happens when I run it.
The values that come up are always either 1, 31, 62, or 92. I've run the program many times, but it keeps generating these numbers. I have some understanding of how random numbers are generated, but this just seems weird. I'll paste the code in below. If someone can explain what's going on here, I would appreciate it greatly. Thanks!
counter=0;
a=0;
b=1;
while(a~=b)do
a=math.random(1,1000000);
b=math.random(1,100);
counter=counter+1;
if(a==b)then
print(a..", "..b..", and it took "..counter.." times")
end
end
The behaviour of the pseudo-random number generator changed in Lua 5.4. The 5.4 Reference Manual states, under §8.2 – Incompatibilities in the Libraries, that
The pseudo-random number generator used by the function math.random now starts with a somewhat random seed. Moreover, it uses a different algorithm.
If you are curious, that new algorithm is xoshiro256**.
What this means is that programs running in Lua environments prior to 5.4 must explicitly call math.randomseed to seed the pRNG. You want to do this only once in your program.
Without seeding the pRNG, the sequence of numbers produced will be the same each time you run your program. This is because, prior to 5.4, Lua's math.random is implemented using C rand or POSIX random, both of which default to a seed of 1 if not explicitly seeded.
The classic way to seed a pRNG is to use the current time (os.time). This is a simple approach, but has the fault that running this program twice in the same second will have the same result.
local counter = 0
local a = 0
local b = 1
math.randomseed(os.time())
while a ~= b do
a = math.random(1, 1000000)
b = math.random(1, 100)
counter = counter + 1
if a == b then
print(a .. ", " .. b .. ", and it took " .. counter .. " times")
end
end
Documentation links, for comparison:
5.3: math.random math.randomseed
5.4: math.random math.randomseed
Some low-level languages like C require the programmer to set seed (usually srand(time(0)) if the user wants a different sequence of random numbers whenever the program runs. If it is not set, the program generates the same sequence of random numbers for each run.
Some high-level languages automatically set the seed if it is not set at first.
In Julia, if I want to generate a new sequence of random numbers each time, should I call srand()?
If you call Julia's srand() without providing a seed, Julia will use system entropy for seeding (essentially using a random seed).
On startup (specifically during initialisation of the Random module), Julia calls srand() without arguments. This means the global RNG is initialised randomly.
That means there's usually no need to call srand() in your own code unless you want to make the point that your random results are not meant to be reproducible.
Julia seeds the random number generator automatically, you use srand with a known seed, in order to recreate the same pseudo random sequence deterministically (useful for testing for example), but if you want to generate a different random sequence each time, all you need is to call rand.
help?> srand
search: srand sprand sprandn isreadonly StepRange StepRangeLen ClusterManager AbstractRNG AbstractUnitRange CartesianRange
srand([rng=GLOBAL_RNG], seed) -> rng
srand([rng=GLOBAL_RNG]) -> rng
Reseed the random number generator: rng will give a reproducible sequence
of numbers if and only if a seed is provided. Some RNGs
don't accept a seed, like RandomDevice. After the call to srand, rng is
equivalent to a newly created object initialized with the
same seed.
This question is about a comment in this question
Recommended way to initialize srand? The first comment says that srand() should be called only ONCE in an application. Why is it so?
That depends on what you are trying to achieve.
Randomization is performed as a function that has a starting value, namely the seed.
So, for the same seed, you will always get the same sequence of values.
If you try to set the seed every time you need a random value, and the seed is the same number, you will always get the same "random" value.
Seed is usually taken from the current time, which are the seconds, as in time(NULL), so if you always set the seed before taking the random number, you will get the same number as long as you call the srand/rand combo multiple times in the same second.
To avoid this problem, srand is set only once per application, because it is doubtful that two of the application instances will be initialized in the same second, so each instance will then have a different sequence of random numbers.
However, there is a slight possibility that you will run your app (especially if it's a short one, or a command line tool or something like that) many times in a second, then you will have to resort to some other way of choosing a seed (unless the same sequence in different application instances is ok by you). But like I said, that depends on your application context of usage.
Also, you may want to try to increase the precision to microseconds (minimizing the chance of the same seed), requires (sys/time.h):
struct timeval t1;
gettimeofday(&t1, NULL);
srand(t1.tv_usec * t1.tv_sec);
Random numbers are actually pseudo random. A seed is set first, from which each call of rand gets a random number, and modifies the internal state and this new state is used in the next rand call to get another number. Because a certain formula is used to generate these "random numbers" therefore setting a certain value of seed after every call to rand will return the same number from the call. For example srand (1234); rand (); will return the same value. Initializing once the initial state with the seed value will generate enough random numbers as you do not set the internal state with srand, thus making the numbers more probable to be random.
Generally we use the time (NULL) returned seconds value when initializing the seed value. Say the srand (time (NULL)); is in a loop. Then loop can iterate more than once in one second, therefore the number of times the loop iterates inside the loop in a second rand call in the loop will return the same "random number", which is not desired. Initializing it once at program start will set the seed once, and each time rand is called, a new number is generated and the internal state is modified, so the next call rand returns a number which is random enough.
For example this code from http://linux.die.net/man/3/rand:
static unsigned long next = 1;
/* RAND_MAX assumed to be 32767 */
int myrand(void) {
next = next * 1103515245 + 12345;
return((unsigned)(next/65536) % 32768);
}
void mysrand(unsigned seed) {
next = seed;
}
The internal state next is declared as global. Each myrand call will modify the internal state and update it, and return a random number. Every call of myrand will have a different next value therefore the the method will return the different numbers every call.
Look at the mysrand implementation; it simply sets the seed value you pass to next. Therefore if you set the next value the same everytime before calling rand it will return the same random value, because of the identical formula applied on it, which is not desirable, as the function is made to be random.
But depending on your needs you can set the seed to some certain value to generate the same "random sequence" each run, say for some benchmark or others.
Short answer: calling srand() is not like "rolling the dice" for the random number generator. Nor is it like shuffling a deck of cards. If anything, it's more like just cutting a deck of cards.
Think of it like this. rand() deals from a big deck of cards, and every time you call it, all it does is pick the next card off the top of the deck, give you the value, and return that card to the bottom of the deck. (Yes, that means the "random" sequence will repeat after a while. It's a very big deck, though: typically 4,294,967,296 cards.)
Furthermore, every time your program runs, a brand-new pack of cards is bought from the game shop, and every brand-new pack of cards always has the same sequence. So unless you do something special, every time your program runs, it will get exactly the same "random" numbers back from rand().
Now, you might say, "Okay, so how do I shuffle the deck?" And the answer -- at least as far as rand and srand are concerned -- is that there is no way of shuffling the deck.
So what does srand do? Based on the analogy I've been building here, calling srand(n) is basically like saying, "cut the deck n cards from the top". But wait, one more thing: it's actually start with another brand-new deck and cut it n cards from the top.
So if you call srand(n), rand(), srand(n), rand(), ..., with the same n every time, you won't just get a not-very-random sequence, you'll actually get the same number back from rand() every time. (Probably not the same number you handed to srand, but the same number back from rand over and over.)
So the best you can do is to cut the deck once, that is, call srand() once, at the beginning of your program, with an n that's reasonably random, so that you'll start at a different random place in the big deck each time your program runs. With rand(), that really is the best you can do.
[P.S. Yes, I know, in real life, when you buy a brand-new deck of cards it's typically in order, not in random order. For the analogy here to work, I'm imagining that each deck you buy from the game shop is in a seemingly random order, but the exact same seemingly-random order as every other deck of cards you buy from that same shop. Sort of like the identically shuffled decks of cards they use in bridge tournaments.]
Addendum: For a very cute demonstration of the fact that for a given PRNG algorithm and a given seed value, you always get the same sequence, see this question (which is about Java, not C, but anyway).
The reason is that srand() sets the initial state of the random generator, and all the values that generator produces are only "random enough" if you don't touch the state yourself in between.
For example you could do:
int getRandomValue()
{
srand(time(0));
return rand();
}
and then if you call that function repeatedly so that time() returns the same values in adjacent calls you just get the same value generated - that's by design.
A simpler solution for using srand() for generating different seeds for application instances run at the same second is as seen.
srand(time(NULL)-getpid());
This method makes your seed very close to random as there is no way to guess at what time your thread started and the pid will be different also.
srand seeds the pseudorandom number generator. If you call it more than once, you will reseed the RNG. And if you call it with the same argument, it will restart the same sequence.
To prove it, if you do something simple like this, you will see the same number printed 100 times:
#include <stdlib.h>
#include <stdio.h>
int main() {
for(int i = 0; i != 100; ++i) {
srand(0);
printf("%d\n", rand());
}
}
It seems that every time rand() runs, it will set a new seed for the next rand().
If srand() runs multiple times, the problem is if the two running happen in one second (the time(NULL) does not change), the next rand() will be the same as the rand() right after the previous srand().
I am using the rgsl library in Rust that wraps functions from the C GSL math libraries. I was using a random number generator function, but I am always getting the same exact value whenever I generate a new random number. I imagine that the number should vary upon each run of the function. Is there something that I am missing? Do I need to set a new random seed each time or such?
extern crate rgsl;
use rgsl::Rng;
fn main() {
rgsl::RngType::env_setup();
let t = rgsl::rng::default();
let r = Rng::new(&t).unwrap()
let val = rgsl::randist::binomial::binomial(&r, 0.01f64, 1u32);
print!("{}",val);
}
The value I keep getting is 1, which seems really high considering the probability of obtaining a 1 is 0.01.
The documentation for env_setup explains everything you need to know:
This function reads the environment variables GSL_RNG_TYPE and GSL_RNG_SEED and uses their values to set the corresponding library variables gsl_rng_default and gsl_rng_default_seed
If you don’t specify a generator for GSL_RNG_TYPE then gsl_rng_mt19937 is used as the default. The initial value of gsl_rng_default_seed is zero.
(Emphasis mine)
Like all software random number generators, this is really an algorithm that produces pseudo random numbers. The algorithm and the initial seed uniquely identify a sequence of these numbers. Since the seed is always the same, the first (and second, third, ...) number in the sequence will always be the same.
So if I want to generate a new series of random numbers, then I need to change the seed each time. However, if I use the rng to generate a set of random seeds, then I will get the same seeds each time.
That's correct.
Other languages don't seem to have this constraint, meaning that the seed can be manually set if desired, but is otherwise is random.
A classical way to do this is to seed your RNG with the current time. This produces an "acceptable" seed for many cases. You can also get access to true random data from the operating system and use that as a seed or mix it in to produce more random data.
Is there no way to do this in Rust?
This is a very different question. If you just want a random number generator in Rust, use the rand crate. This uses techniques like I described above.
You could even do something crazy like using random values from the rand crate to seed your other random number generator. I just assumed that there is some important reason you are using that crate instead of rand.
Today, my friend had a thought that setting the seed of a pseudo-random number generator multiple times using the pseudo-random number generated to "make things more randomized".
An example in C#:
// Initiate one with a time-based seed
Random rand = new Random(milliseconds_since_unix_epoch());
// Then loop for a_number_of_times...
for (int i = 0; i < a_number_of_times; i++)
{
// ... to initiate with the next random number generated
rand = new Random(rand.Next());
}
// So is `rand` now really random?
assert(rand.Next() is really_random);
But I was thinking that this could probably increase the chance of getting a repeated seed being used for the pseudo-random number generator.
Will this
make things more randomized,
making it loop through a certain number of seeds used, or
does nothing to the randomness (i.e. neither increase nor decrease)?
Could any expert in pseudo-random number generators give some detailed explanations so that I can convince my friend? I would be happy to see answers explaining further detail in some pseudo-random number generator algorithm.
There are three basic levels of use for pseudorandom numbers. Each level subsumes the one below it.
Unexpected numbers with no particular correlation guarantees. Generators at this level typically have some hidden correlations that might matter to you, or might not.
Statistically-independent number with known non-correlation. These are generally required for numerical simulations.
Cryptographically secure numbers that cannot be guessed. These are always required when security is at issue.
Each of these is deterministic. A random number generator is an algorithm that has some internal state. Applying the algorithm once yields a new internal state and an output number. Seeding the generator means setting up an internal state; it's not always the case that the seed interface allows setting up every possible internal state. As a good rule of thumb, always assume that the default library random() routine operates at only the weakest level, level 1.
To answer your specific question, the algorithm in the question (1) cannot increase the randomness and (2) might decrease it. The expectation of randomness, thus, is strictly lower than seeding it once at the beginning. The reason comes from the possible existence of short iterative cycles. An iterative cycle for a function F is a pair of integers n and k where F^(n) (k) = k, where the exponent is the number of times F is applied. For example, F^(3) (x) = F(F(F(x))). If there's a short iterative cycle, the random numbers will repeat more often than they would otherwise. In the code presented, the iteration function is to seed the generator and then take the first output.
To answer a question you didn't quite ask, but which is relevant to getting an understanding of this, seeding with a millisecond counter makes your generator fail the test of level 3, unguessability. That's because the number of possible milliseconds is cryptographically small, which is a number known to be subject to exhaustive search. As of this writing, 2^50 should be considered cryptographically small. (For what counts as cryptographically large in any year, please find a reputable expert.) Now the number of milliseconds in a century is approximately 2^(41.5), so don't rely on that form of seeding for security purposes.
Your example won't increase the randomness because there is no increase in entropy. It is simply derived from the execution time of the program.
Instead of using something based of the current time, computers maintain an entropy pool, and build it up with data that is statistically random (or at least, unguessable). For example, the timing delay between network packets, or key-strokes, or hard-drive read times.
You should tap into that entropy pool if you want good random numbers. These are known as Cryptographically secure pseudorandom number generators.
In C#, see the Cryptography.RandomNumberGenerator Class for the right way to get a secure random number.
This will not make things more "random".
Our seed determines the random looking but completely determined sequence of numbers that rand.next() gives us.
Instead of making things more random, your code defines a mapping from your initial seed to some final seed, and, given the same initial seed, you will always end up with the same final seed.
Try playing with this code and you will see what I mean (also, here is a link to a version you can run in your browser):
int my_seed = 100; // change my seed to whatever you want
Random rand = new Random(my_seed);
for (int i = 0; i < a_number_of_times; i++)
{
rand = new Random(rand.Next());
}
// does this print the same number every run if we don't change the starting seed?
Console.WriteLine(rand.Next()); // yes, it does
The Random object with this final seed is just like any other Random object. It just took you more time then necessary to create it.