Generate Array of Numbers that fit to a Probability Distribution in Ruby?

Say I have 100 records, and I want to mock out the created_at date so it fits on some curve. Is there a library to do that, or what formula could I use? I think this is along the same track:

Generate Random Numbers with Probabilistic Distribution

I开发者_如何学JAVA don't know much about how they are classified in mathematics, but I'm looking at things like:

• bell curve
• logarithmic (typical biology/evolution) curve? ...

Just looking for some formulas in code so I can say this:

• Given 100 records, a timespan of 1.week, and an interval of 12.hours
• set created_at for each record such that it fits, roughly, to curve

Thanks so much!

Update

I found this forum post about ruby algorithms, which led me to rsruby, an R/Ruby bridge, but that seems like too much.

Update 2

I wrote this little snippet trying out the gsl library, getting there...

Generate test data in Rails where created_at falls along a Statistical Distribution

I recently came across croupier, a ruby gem that aims to generate numbers according to a variety of statistical distributions.

I have yet to try it but it sounds quite promising.

You can generate UNIX timestamps which are really just integers. First figure out when you want to start, for example now:

start = DateTime::now().to_time.to_i

Find out when the end of your interval should be (say 1 week later):

finish = (DateTime::now()+1.week).to_time.to_i

Ruby uses this algorithm to generate random numbers. It is almost uniform. Then generate random numbers between the two:

r = Random.new.rand(start..finish)

Then convert that back to a date:

d = Time.at(r)

This looks promising as well: http://rb-gsl.rubyforge.org/files/rdoc/randist_rdoc.html

And this too: http://rb-gsl.rubyforge.org/files/rdoc/rng_rdoc.html

From wiki:

There are a couple of methods to generate a random number based on a probability density function. These methods involve transforming a uniform random number in some way. Because of this, these methods work equally well in generating both pseudo-random and true random numbers.

One method, called the inversion method, involves integrating up to an area greater than or equal to the random number (which should be generated between 0 and 1 for proper distributions).

A second method, called the acceptance-rejection method, involves choosing an x and y value and testing whether the function of x is greater than the y value. If it is, the x value is accepted. Otherwise, the x value is rejected and the algorithm tries again.

The first method is the one used in the accepted answer in your SO linked question: Generate Random Numbers with Probabilistic Distribution

Another option is the Distribution gem under SciRuby. You can generate normal numbers by:

require 'distribution'

rng = Distribution::Normal.rng
random_numbers = Array.new(100).map { rng.call }

There are RNGs for various other distributions as well.