Trigonometric functions are costly operations and can slow down your application if they are extensively used. There are two reasons why: First, Math.sin() is a function, and thus needs a function call which simple eats up some time. Second, the result is computed with much more precision than you would ever need in most situations.

Most often you just want the periodic wave-like characteristics of the sine or cosine, which can be approximated in various ways. One common way of making it faster is to create a *lookup-table* by computing the sine at discrete steps and storing the result in an array. For example:

var sineTable:Array = []; for (var i:int = 0; i < 90; i++) { sineTable[i] = Math.sin(Math.PI/180 * i) }

Due to the symmetry of the sine wave, it’s sufficient to compute one quadrant only (0..pi/2), and the other 3/4’s of the circle can be computed by shifting and wrapping the input value. The biggest drawback is that the values are stored at a fixed resolution and so the result is not very accurate. This can be enhanced with linear interpolation:

x = 22.5; y = sineTable[int(x)] + (sineTable[int(x + .5)] - sineTable[int(x)]) / 2;

Much better, but yet the error exists. It also involves accessing array elements which makes the code rather slow. Another technique uses *taylor series approximation*:

sin(x) = x - (x^3)/3! + (x^5)/5! - (x^7)/7! + ...

Like with the lookup-table, evaluating this term is costly.

After searching for alternatives, I finally found a fantastic solution using a quadratic curve which blows everything away in terms of performance *and* accuracy. For a detailed derivation, please follow the link because I won’t go into it.

I did minor optimizations to figure out what AS3 likes most, and arrived at some code that can be up to 14x faster, while still being very accurate. However, you have to use it directly – do not place the code inside a function, because the additional function call sweeps out the performance gain, and you are left with an approximation that is actually *slower* compared to a native Math.sin() or Math.cos() call. Also note that cos(x) = sin(x + pi/2) or cos(x – pi/2) = sin(x), so computing the cosine is just of matter adding pi/2 to the input value.

Download source: fastTrig.as.

Below is a simple visualization to show you the quality of the approximation. The high precision version can replace the Math.sin() and Math.cos() calls in nearly all situations.

### Low precision sine/cosine (~14x faster)

//always wrap input angle to -PI..PI if (x < -3.14159265) x += 6.28318531; else if (x > 3.14159265) x -= 6.28318531; //compute sine if (x < 0) sin = 1.27323954 * x + .405284735 * x * x; else sin = 1.27323954 * x - 0.405284735 * x * x; //compute cosine: sin(x + PI/2) = cos(x) x += 1.57079632; if (x > 3.14159265) x -= 6.28318531; if (x < 0) cos = 1.27323954 * x + 0.405284735 * x * x else cos = 1.27323954 * x - 0.405284735 * x * x; }

### High precision sine/cosine (~8x faster)

//always wrap input angle to -PI..PI if (x < -3.14159265) x += 6.28318531; else if (x > 3.14159265) x -= 6.28318531; //compute sine if (x < 0) { sin = 1.27323954 * x + .405284735 * x * x; if (sin < 0) sin = .225 * (sin *-sin - sin) + sin; else sin = .225 * (sin * sin - sin) + sin; } else { sin = 1.27323954 * x - 0.405284735 * x * x; if (sin < 0) sin = .225 * (sin *-sin - sin) + sin; else sin = .225 * (sin * sin - sin) + sin; } //compute cosine: sin(x + PI/2) = cos(x) x += 1.57079632; if (x > 3.14159265) x -= 6.28318531; if (x < 0) { cos = 1.27323954 * x + 0.405284735 * x * x; if (cos < 0) cos = .225 * (cos *-cos - cos) + cos; else cos = .225 * (cos * cos - cos) + cos; } else { cos = 1.27323954 * x - 0.405284735 * x * x; if (cos < 0) cos = .225 * (cos *-cos - cos) + cos; else cos = .225 * (cos * cos - cos) + cos; }