random number generator no repeats

1. Seeds and distribution Five types of distributions are introduced here, including the following: (a), and (). Parameters required for distribution and use are provided. 2. Test the random number generator. This section contains only one simple example, which is not described in detail. The following is the procedure for getting a

A whole bunch of borders was not known at first, and after a few random sentences, WAHelpless to download the data, and then crazy to judge all kinds of strange boundariesTo gouge out the boundary problemFirst we consider the situation of a=1X1+k*b=t (mod p)EX_GCD can be solvedConsider the situation of a>1Make s=x+b/(A-1)The original is becoming a geometric series.S1*a^k= (t+b/(A-1)) (mod p)BSGS solution after moving the itemAll other boundaries can b

Prioritize the processing of arrays in the way it describesAnd then, in order to get as many small numbers as possible in the sequence,So 1 is a must to appear, in order to make the whole sequence of the order of the dictionary after the smallest.We thought, if 2 could be in this series, it'd be better.But 2 may not be in this series, that is, 2 walk 1 is impossible to go to the place, you can not walk 2.So from small to large enumeration numbers, if the current

; - } -T/=D; the ll x, y; the EXGCD (a,b,x,y); thex= (x*t)%p; the while(x0) x+=p; - returnx+1; the } thell C=pow (A-1, P-2); thell a= (b*c+x1)%p,b=p,t= (b*c+t)%p;94 if(a0) a= (a+p)%p; the if(b0) b= (b+p)%p; thell d=gcd (A, b); the if(t%D) {98 return-1; About } -T/=D;101 ll x, y;102 EXGCD (a,b,x,y);103 while(x0) x= (x+p)%p;104x= (x*t)%p; thell ans=Work (a,x);106 if(ans!=-1)returnans+1;107 Else returnans;108 }109 intMain

, regularity. From this point of view, you will probably accept the fact that the computer can only produce pseudo-random numbers and not produce absolutely random random numbers. First, let's look at the concepts of true random numbers and pseudo-random numbers. True

Simple Example of Python2 random series generator and python2 series Generator This article describes the Python2 random series generator. We will share this with you for your reference. The details are as follows: # Filename: randNumber. pyimport randomwhile True: try: ro

follow any laws. For example, "There are no two leaves in the same shape," which is the characteristics of things, that is, randomness, but the leaves of each tree have an approximate shape, which is the commonness of things, that is, regularity. From this point of view, you will probably accept the fact that computers can only produce pseudo random numbers and cannot produce random numbers that are absolu

can only produce pseudo random numbers and cannot produce random numbers that are absolutely random. First, let's take a look at the concept of true random numbers and pseudorandom numbers. True random number

regular meaning, that is, the pseudo-random numbers produced by computers are both random and regular. How can this problem be understood? The generated pseudo-random numbers sometimes follow certain rules, and sometimes do not follow any rules. Some pseudo-random numbers follow certain rules, while others do not foll

, while others do not follow any rules. For example, "there are no two leaves in the same shape in the world." This is just the characteristic of things, that is, randomness. However, the leaves of every tree have an approximate shape. this is the commonality of things, regularity. From this perspective, you will probably accept the fact that a computer can only generate pseudo-random numbers instead of absolute r