Cellular Automata

Web: https://aperocky.com/cellular-automata/, this simulation runs entirely in client.

Creating a cellular automata with a couple lines of descriptive language and watch how it evolves:

^^ Logo generated using slightly modified Generate Pretty Logo example.

Use descriptive conditions described in json to control a simulation:

{
    "InitialCondition": "1 0.2",
    "0": [
        "CountAdjacent eq 1 3 1"
    ],
    "1": [
        "CountAdjacent lt 1 2 0",
        "CountAdjacent gt 1 3 0"
    ]
}

^^ This correspond to conway's game of life, with initial map being generated at 20% "filled".

{
  "0": [
    "SpontaneousChange 1 0.02",
    "CountAdjacentChance gt 1 0 1 0.1"
  ],
  "1": [
    "SpontaneousChange 2 0.002",
    "CountAdjacent gt 2 0 2"
  ],
  "2": [
    "SpontaneousChange 0 1"
  ],
  "colorMap": {
    "0": "black",
    "1": "green",
    "2": "red"
  },
  "timeStep": 100
}

This correspond to a forest fire (more complex);

More examples: https://github.com/Aperocky/cellular-automata/tree/main/sample

Functions

---

CountAdjacent [comparison-operator] [target] [threshold] [destination]
CountDirectlyAdjacent [comparison-operator] [target] [threshold] [destination]

This compares the total adjacent blocks that are target with threshold to determine if it will changes to destination. Adjacent counts 8 neighboring cells, DirectlyAdjacent only counts the 4 blocks in cardinal directions.

CountAdjacentChance [comparison-operator] [target] [threshold] [destination] [chance]
CountDirectlyAdjacentChance [comparison-operator] [target] [threshold] [destination] [chance]

This compares the total adjacent blocks that are target with threshold to determine if it will changes to destination, however, it only does so on chance.

SpontaneousChange [destination] [chance]

This will change into destination on chance.

ChangeByBlockAge [comparison-operator] [threshold] [destination] [chance]

This will change the block by comparing the age of the block (when it remains the same) against the threshold, and if satisfy the comparison, will change into destination on chance.

InitialCondition

---

There are a few initial condition available:

When there are no initialCondition in the map, the map is initiated as all 0s.

"initialCondition": "[INITIAL_CONDITION]"

When INITIAL_CONDITION is in the format of:

"1 0.2": all blocks in the map will have 1 with a possibility of 20%

"CentralDot 1": A single 1 in the center.

"CentralSquare 1": A square of 1 (2x2) in the center, this is also perfectly in the middle of the whole map (100x100)

"cornerDot 1": A dot of 1 in the top left corner

Anatomy of the json file

---

{
    "InitialCondition": "1 0.2",

Currently I only support 1 kind of initial value that are not zero, the first one being target.

    "0": [
        "CountAdjacent eq 1 3 1"
    ],
    "1": [
        "CountAdjacent lt 1 2 0",
        "CountAdjacent gt 1 3 0"
    ]

list of function associated with the current values in the locations, these 3 means:

• If this square is 0, Count All Adjacent 1s, if it equals 3, make the value 1.
• If this square is 1, Count All Adjacent 1s, if it is less than 2, make the value 0.
• If this square is 1, Count All Adjacent 1s, if it is greater than 3, make the value 0.

    "colorMap": {
        "0": "black",
        "1": "red"
    },
    "timestep": 100,
}

There is a default color map, you can make your own too. However, custom colormap need to cover all cases.

timestep are measured in milliseconds.