Reputation: 4721
Except using look-up tables, is there another way to optimize the parameterization algorithm of a cubic Bézier curve like this? (5000 steps for a good parameterization is simply too much for a slower PC, as I need to call this function many times in 1 second):
function parameterizeCurve(path, partArc, initialT)
{
// curve length is already known and globally defined
// brute force
var STEPS = 5000; // > precision
var t = 1 / STEPS;
var aX=0;
var aY=0;
var bX=path[0], bY=path[1];
var dX=0, dY=0;
var dS = 0;
var sumArc = 0;
var arrT = new Array(Math.round(partArc));
var z = 1;
arrT[0] = -1;
var oldpartArc = partArc;
partArc = partArc - initialT;
var j = 0;
for (var i=0; i<STEPS; j = j + t) {
aX = bezierPoint(j, path[0], path[2], path[4], path[6]);
aY = bezierPoint(j, path[1], path[3], path[5], path[7]);
dX = aX - bX;
dY = aY - bY;
// deltaS. Pitagora
dS = Math.sqrt((dX * dX) + (dY * dY));
sumArc = sumArc + dS;
if (sumArc >= partArc) {
arrT[z] = j; // save current t
z++;
sumArc = 0;
partArc = oldpartArc;
}
bX = aX;
bY = aY;
i++;
}
return arrT;
}
function bezierPoint(t, o1, c1, c2, e1) {
var C1 = (e1 - (3.0 * c2) + (3.0 * c1) - o1);
var C2 = ((3.0 * c2) - (6.0 * c1) + (3.0 * o1));
var C3 = ((3.0 * c1) - (3.0 * o1));
var C4 = (o1);
return ((C1*t*t*t) + (C2*t*t) + (C3*t) + C4)
}
Upvotes: 2
Views: 948
Reputation: 2363
If I've guessed correctly, you're trying to come up with a cubic Bezier curve parameterization that moves at a constant speed along the curve.
So, why do you need 5000 steps? The minimum one can move along a curve is one pixel. A Bezier stays within the convex hull of its four control points, so the length of the curve will be less than that of the polyline P0 -> P1 -> P2 -> P3
. So find that length in pixels, and use it (instead of 5000).
Let me know if that speeds things up enough.
Upvotes: 1