Conway's Game of Life 3D

This repository is both provides an API for Game of Life and an command line application interface to use the API. I built the API and the algorithm just for fun and learn new things. I hope you'll like it.

Note that, there may be lots of bugs and lots of performance issues, if you want to contribute it, I would be very happy.

Installation

Dependency	Installation
Python3	https://www.python.org/downloads/
numpy	via pip: pip install numpy
matplotlib (for 3D)	via pip: pip install matplotlib
mayavi (for 3D) (Use the bleeding edge version.)	https://github.com/enthought/mayavi#bleeding-edge

I recommend you to use virtual enviroment for application. You may have noticed that requirements.txt file does not have mayavi since I want you to use it's bleeding edge version. If the pip version of mayavi works with your system, tell me or update the README.md file.

Detailed Explaination of Installing

~$ git clone https://github.com/electricalgorithm/3D-Conways-Game-of-Life.git
~$ cd 3D-Conways-Game-of-Life
~$ virtualenv . # I had used Python 3.7 to develop the project. You can specify it with `--python=path/to/python3.7`
~$ source bin/active # For Windows users, it think it's ".\Scripts\activate".
~$ pip install numpy
~$ pip install matplotlib
# Installing of mayavi bleeding edge
~$ git clone https://github.com/enthought/mayavi.git
~$ cd mayavi
~$ pip install -r requirements.txt
~$ pip install PyQt5
~$ python setup.py install
# Returning back to main.py directory.
# Opening the program.
~$ python main.py --row=3 --col=3 --page=2 --gen=2 --renderer=mayavi

Using as application

The application requires using flags to simulate. They are:

• --row= Required. Must be an integer. It sets the Game of Life's row/y dimension for randomizing values. The life's grid won't be restricted to these dimensions.
• --col= Required. Must be an integer. It sets the Game of Life's col/x dimension for randomizing values. The life's grid won't be restricted to these dimensions.
• --page= Required. Must be an integer. It sets the Game of Life's page/z dimension for randomizing values. The life's grid won't be restricted to these dimensions.
• --gen= Required. Must be an integer. It is the number of the generations which will be calculated. For higher numbers, the simulation will be very slow. Consider changing LENGTH_EXPAND_RATE constant with a lower value in Space.py file.
• --chance= Optional. Must be an integer. It defines the chance of randomize() function as one over given integer.
• --rules= Optional. Default is "B3/S23". It defines the ruleset.
• --waitms= Optional. Must be an integer. This is the delay in the calculations of the generations. Don't sure if it works correctly, check it out.
• --renderer= Optional. Must be mayavi, matplotlib or matplotlib:1by1. This the rendering method of 3D view. If not spesified, nothing will pop-up to show you the generations.
• --save= Optional. Default is True. Must be True or False. To do not save matplotlib figures, make it False.
• --save-prefix= Optional. Default is GoL. The prefix for saving matplotlib figures.

Example

~$ python main.py --row=5 --col=5 --page=4 --chance=4 --rules=B36/S23 --gen=2 --renderer=matplotlib:1by1 --save=True --save-prefix=GoL-example

Note: If you use 1by1 method, you have to close the current figure window to see next generation.

API

Class
VoxelCell (VoxelCell.py)	The cell class for using in Space.
Space (Space.py)	The class for creating the game.

Methods of VoxelCell class
VoxelClass(row, col, page)	It creates a VoxelCell object with given positions.
set_alive()	It revitalizes (set the cell alive) the VoxelCell.
set_dead()	It kills (set the cell dead) the VoxellCell.
is_alive()	Returns True if the VoxelCell is living.
get_numeric_alive()	Same as is_alive but returns int instead of bool.
get_coordinates()	It returns VoxelCell's indices in the instance of Space.

Methods of Space class
Space(row_count, col_count, page_count, chance_1_divided_by=3, restricted_page=None)	It creates a Space object which has row_count * col_count * page_count VoxelCell instances. Note that, after the creation, the cell expands. It should be fixed for new versions. restricted_page doesn't work for now.
expand()	Expands the Space object's grid.
export(seperate_dims)	Returns the Space grid as numpy.ndarray. If seperate_dims given as True, it returns a tuple of numpy.ndarray.
randomize()	It randomly sets the VoxelCells alive.
set_cell(indices, status)	It sets the VoxelCell at (page, row, col) indices as status which must be "alive" or "dead".
set_rules(rules)	Default: "B3/S23". It changes the ruleset for Game of Life.
update()	It creates new generation. Note: New generation will be assigned to the current _grid property.
static: clear_ndarray(tdarray, override=False)	Clears all the non-neccecary (which is whole dimension is 0/dead) VoxelCells. It may use for another purposes too. Note: Works only for 3D numpy.ndarray objects.
static: combine_two_grid(expanded_grid, small_grid: list, small_g_size, expand_rate)	It combines two grid (3D nested list) while preserving their living status.
static: create_grid(pages, rows, cols)	Creates a 3D nested list which has VoxelCell objects.
static: get_dimensions(nested_list)	Returns a 3D nested list (or a grid)'s dimensions.

Functions of Utils.py
create_matplotlib_graphs(space_object, generations, save=(False, None), show=True, onebyone=False)	To show 3D projections of the Space object with using matplotlib. If onebyone is True, it'll create every generation in a new window. If it is False, they will be in a window/figure together.
create_mayavi_animation(space_object, generations, wait, ui=False)	To show 3D projection of Space object as a animation with using mayavi. Notice that, while the function calculates newer generations you can't change the position of the camera. It should be fixed in new versions.

Example Usage of the API

from Space import Space
from utils import create_matplotlib_graphs

# Creates the Life (or Space instance)
Life = Space(5, 5, 4, chance_1_divided_by=4)
# Randomly sets the VoxelCells in the grid alive.
Life.randomize()
# Set the VoxelCell at (6, 5, 3) alive.
Life.set_cell((6, 5, 3), "alive")
# Calculate the next generation.
Life.update()
# Save the figures of generation and the next one with using matplotlib and show them as seperate windows.
create_matplotlib_graphs(Life, 2, save=(True, "GoL-example"), show=True, onebyone=True)
# All done.