He had been relayed Campos' report that an L-bracket was blocking an exit door and went to check it out. He inadvertently became a hero by pinpointing the exact location of the shooter.Īt 10:08 p.m., Stephen Schuck, a Mandalay Bay maintenance engineer, got off an elevator on the 32nd floor. ![]() Had that not occurred, Campos would not have stumbled upon the massacre at the precise moment it was commencing. The original alarm call turned out to be a nanny who had left her room door ajar. "Hey, there's shots fired in 32-135," he reported. I went to lift up my pant leg and I saw the blood coming down."įinding cover in an alcove, Campos radioed for help at 10:06 p.m. "I had to take a moment to realize what was going on. PRNG( seed ) /// Output will be the same."I was struck and I went to get cover," Campos said. Seed( 1234 ) /// Seed reset for ten iterations! However, the seed must only be set once before using the algorithm itself! /// Proper way! Hence, why the term pseudo-random is utilized to be more pedantically correct!īefore you can actually use a PRNG, i.e., pseudo-random number generator, you must provide the algorithm with an initial value often referred too as the seed. I say approximately resemble, because true randomness is a rather elusive mystery in mathematics and computer science. Pseudo-random number generation involves the process of utilizing a deterministic algorithm that produces a sequence of numbers whose properties approximately resemble random numbers. Whenever you do a basic web search for random number generation in the C++ programming language this question is usually the first to pop up! I want to throw my hat into the ring to hopefully better clarify the concept of pseudo-random number generation in C++ for future coders that will inevitably search this same question on the web! The Basics Std::uniform_int_distribution distrib(1, 6) įor( unsigned long j = 0 j < 100500 ++j ) Std::chrono::high_resolution_clock::now().time_since_epoch() Std::chrono::system_clock::now().time_since_epoch() Old-fashioned C code example based on the same srand()/rand()/time() functions that was used in the question: #include įor( j = 0 j RAND_MAX - (RAND_MAX-5)%6 ) Obviously when you happen to run application on the same second - you use the same seed value - thus your result is the same of course (as Martin York already mentioned in a comment to the question).Īctually you should call srand(seed) one time and then call rand() many times and analyze that sequence - it should look random.Īpparently verbal description is not enough (maybe language barrier or something. ![]() What do you expect to see on output then? It means that if you pass the same value to srand in two different applications (with the same srand/ rand implementation) then you will get exactly the same sequence of rand() values read after that in both applications.īUT in your example application pseudo-random sequence consists only of one element - the first element of a pseudo-random sequence generated from seed equal to current time of 1 sec precision. The whole point of srand function is to initialize the sequence of pseudo-random numbers with a random seed. The most fundamental problem of your test application is that you call srand once and then call rand one time and exit.
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