I’ve never been too happy with the random number generation capabilities of Parrot. Parrot essentially provides a thin wrapper around the system rand and srand capabilities, with an unimaginative interface. This is a fine system for most purposes, but sometimes you need something a little bit different, or want to substitute your own version without too much hassle.

One of the tasks I submitted to GCI was asking for an implementation of the Mersenne Twister algorithm, a good and well-known algorithm to generate pseudo-random numbers. GCI student Yuki’N, who was also a prolific contributor last year for the program, submitted a fine implementation for Rosella to use. Shortly thereafter I wrote up a quick Box-Muller implementation to get normally-distributed numbers too. Now, Rosella has a pretty decent start of a random number library.

For an example I wrote up a short histogram program to display the output. Here are the histograms for the Mersenne Twister and the Box-Muller generators:

Histogram of 500 uniformly-distributed floats:
0: ##########################
1: ####################
2: ##########################
3: ##########################
4: #############################
5: #########################
6: ###########################
7: ########################
8: ####################
9: #######################
10: ############################
11: ##############
12: ###############################
13: #########################
14: ##############
15: ##########################
16: ##########################
17: ##############
18: ##############################
19: #######################

Histogram of 500 normal-distributed floats:
0: #
1: #
2: ####
3: ######
4: ########
5: ########################
6: #######################
7: #########################################################
8: ##########################################################################
9: ###################################################################
10: ################################################################
11: ####################################################
12: #######################################################
13: #########################
14: #################
15: ########
16: ##########
17: #
18:
19: ##

These are the two distributions that I wanted to have most, but they are certainly not the only one ones available.

And random number generation is not the only feature that this library will have, either. The Rosella Query library currently had an implementation of a Fisher-Yates Shuffle algorithm for shuffling an array. I moved that implementation to the new Random library already and updated it to use the Mersenne Twister as the random number source instead of Parrot’s built-in rand opcode.

I have got a handful of other small features and additions that I would like to add to this library, but considering that it is so straight-forward and algorithmic I expect I can make it stable pretty soon without much headache.