Calypso88

A big danger when working with large sets of data is the possibility of introducing a small slowdown that's compounded with every piece of data in the set. A common example is the multidimensional array; it's a powerful tool, but every time you look into the array you have to go at least two lookups deep to find your data. Normally that's not a big deal but if you're touching the set thousands of times per frame, it adds up quickly.

A fairly drastic solution is to flatten your arrays - it will give you a nice performance boost when you access the data, but it comes at the cost of obfuscation. Here's how it works:

(Sorry the numbers are goofy between the diagram and the code - CS4 crashed and I didn't feel like re-making that graphic)

In the traditional 2D view each "row" is a new Array object - this is where the added computing cost comes in. By flattening the data into one super-long array, you can access any piece of data with just one lookup. Finding the correct cell is a little more tricky though.

var myMDArray:Array = [
	['0a', '0b', '0c', '0d', '0e'],
	['1a', '1b', '1c', '1d', '1e'],
	['2a', '2b', '2c', '2d', '2e']];
 
var myFlatArray:Array = ['0a', '0b', '0c', '0d', '0e', '1a', '1b', '1c', '1d', '1e', '2a', '2b', '2c', '2d', '2e'];
 
var columns:int = 5;
 
trace(myMDArray[2][4]);
trace(myFlatArray[14]);
trace(myFlatArray[(2 * columns) + 4]);
//  2e, 2e, 2e

Now - supposing you have an index for something and want to reverse engineer the row and column - just break out the modulo grid code:

var row:int = int(14 / columns);
var col:int = 14 % columns;
 
trace(row, col);
//  2, 4