## RNG147

### March 28, 2017

We have looked at random number generators in several previous exercises, but most of them returned integers. In today’s exercise we look at a simple random number generator that returns floating-point numbers. The generator is simple: Given a seed between zero and one, the next number in the sequence is the fractional portion of 147 times the seed.

Your task is to implement the random number generator described above, and to assess its suitability. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

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In python 3

Your sine trick only moves the problem elsewhere; try seeding with pi/6 (arcsin of 1/2).

Solution in Haskell, using the Stream package for explicitly infinite lists:

Here’s another Haskell version. With an integer argument, n, it prints the first n random numbers. With no arguments it converts the stream of random Doubles into a stream of 32-bit unsigned integers. The purpose is to feed that binary data to the dieharder program, which evaluates its randomness. We don’t make use of all the bits in the Double; it’s just an easy way of getting the data to dieharder in a form that it likes.

Here’s the result of feeding the output to dieharder. I won’t try to interpret the results, here. (The -a argument tells it to run all the tests it has; -g 200 says that stdin is a series of 32-bit unsigned integers.) The summary is that 82 tests passed, 27 failed and 5 were weak.

[…] built several random number generators: [1], [2], [3], [4], [5], [6], [7], [8], [9] (I didn’t realize it was so many until I went back and looked). In today’s exercise we […]