Ruby implementation of Conway's Game of Life initiated at Global Day of Coderetreat 2012 Berlin
In case you do not use a Ruby version manager such as RVM or rbenv, the installation will require admin rights and using 'sudo' to install it.
The gem can be installed in the usual ways. Either let bundler take care of it and add to your Gemfile like this:
gem 'golr'
Or install it directly from your command line
gem install golr
An executable ships with this gem, it is called 'golr'.
You can run Golr by specifying a file that contains the initial state of the game. Please find examples of initial game definitions in the folder named 'examples'.
To evolve the game from an initial state given in 'game-file' for e.g. 5 generations, call the executable like this:
golr <game-file> -g5
So for the examples contained in this repo, you could run
golr examples/glider -g500
or
golr examples/lwss -g300
another nice example is the "Pulsar"
golr examples/pulsar
If you do not specify a number of generations, its value will default to 100.
In case you are interested only in the time spent on calculating a certain number of generations, you can add the --time-only option
golr --time-only -g1000 examples/lwss
4.777137s elapsed for 1000 generations
On Unix-like systems, you can combine this with the 'time' command to get more insight into how the elapsed time is split up between User Time and System Time
time golr --time-only -g1000 examples/lwss
4.695895s elapsed for 1000 generations
real 0m5.162s
user 0m5.115s
sys 0m0.037s
Find out more about the options of the 'golr' script by calling
golr -h
The gem has no runtime dependencies. It has been developed in Ruby 1.9.3 and is being continuously integrated in MRI 2.0.0, 1.9.3, 1.8.7 plus jruby-head in 1.9-mode.
- using Arrays for Keys still sub-prime: switch to bin (2s complement)
- use 2-dimensional Array instead of Map -> faster?
- use 1-dimensional Array and Key based on width of Board -> faster? Could use a window (subarray?)
- document setup and validation of grid (gamereader, gameprinter, game)
- Visualization (ncurses, macruby, processing)
- alternative game rules
- Performance benchmarks and optimization (find hotspots, different key types and data structures, exploit sparseness)