javascript 求两点间夹角的最快方法

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时间:2020-10-26 17:24:07  来源:igfitidea点击:

Fastest way to find the angle between two points

javascriptmath

提问by Timothy Eckstein

To increase the speed at which I find the sine/cosine of an angle, I have built a reference table instead of calculating them on the fly. I have the same idea with finding the angle from one point to another.

为了提高我找到角度的正弦/余弦的速度,我建立了一个参考表,而不是即时计算它们。我对找到从一个点到另一个点的角度有同样的想法。

I have created a table of 3600 normalized vectors (3600 / 10 = accuracy of one tenth of a degree). Whenever I need to know the angle from one point to the next, I look through the table to find the best match. However, I am concerned that this might be slower than using math.atan2().

我创建了一个包含 3600 个归一化向量的表(3600 / 10 = 十分之一度的精度)。每当我需要知道从一个点到另一个点的角度时,我都会查看表格以找到最佳匹配。但是,我担心这可能比使用 math.atan2() 慢。

Here is the code I am using:

这是我正在使用的代码:

Create the vector table:

创建向量表:

// vector to angle table
var vectorToAngleTable = new Array();
for (i = 0; i < 3600; i += 1) {
    vectorToAngleTable[i] = new Vector2();
    vectorToAngleTable[i] = RotatePoint(forwardVector, i / 10);
}

Find the angle from two points:

从两点求角度:

function NormalizeVector(vector) {
    var toReturn = vector;
    var dist = Math.sqrt(vector.x * vector.x + vector.y * vector.y);
    toReturn.x /= dist.x;
    toReturn.y /= dist.y;
    return toReturn;
}

function PointDirection(position, target) {
    var vector = target;
    var toReturn = 0;
    var smallest = 1.0;
    vector.x -= position.x;
    vector.y -= position.y;
    vector = NormalizeVector(vector);
    for (i = 0; i < 3600; i += 1) {
        if (PointDistance(vectorToAngleTable[i], vector) < smallest) {
            smalllest = PointDistance(vectorToAngleTable[i], vector);
            toReturn = i;
        }
    }
    return toReturn;
}

function PointDistance(point1, point2) {
    return Math.sqrt(((point2.x - point1.x) * (point2.x - point1.x)) + ((point2.y - point1.y) * (point2.y - point1.y)));
}

As you can see, my concern is all the lines of code it is going through, and how many entries there are on the table that it looks through. I would love to know the fastest way to find the angle, no matter what the method is.

正如您所看到的,我关心的是它经过的所有代码行,以及它查看的表上有多少条目。我很想知道找到角度的最快方法,无论使用什么方法。

回答by Paul S.

As angle(v1, v2) = acos( (v1x * v2x + v1y * v2y) / (sqrt(v1x^2+v1y^2) * sqrt(v2x^2+v2y^2)) )and we know v2 = [1, 0]

正如angle(v1, v2) = acos( (v1x * v2x + v1y * v2y) / (sqrt(v1x^2+v1y^2) * sqrt(v2x^2+v2y^2)) )我们所知v2 = [1, 0]

var v = {x: 0, y: 1},
    angleRad = Math.acos( v.x / Math.sqrt(v.x*v.x + v.y*v.y) ),
    angleDeg = angleRad * 180 / Math.PI;

where vis the vector [point2.x - point1.x , point2.y - point1.y]

v向量在哪里[point2.x - point1.x , point2.y - point1.y]



Edit - I just realised you may have meant treat each point as a vector, in which case it'd be

编辑 - 我刚刚意识到你可能想把每个点都当作一个向量,在这种情况下它会是

var v1 = {x: 0, y: 1}, v2 = {x: 1, y: 0},
    angleRad = Math.acos( (v1.x * v2.x + v1.y * v2.y) / ( Math.sqrt(v1.x*v1.x + v1.y*v1.y) * Math.sqrt(v2.x*v2.x + v2.y*v2.y) ) ),
    angleDeg = angleRad * 180 / Math.PI;

where v1is the vector [point1.x , point1.y]and v2is [point2.x , point2.y]

哪里v1是向量[point1.x , point1.y]v2[point2.x , point2.y]



Edit 2
To speed up if you're using the vectors length many times, save it as e.g. v.length = ...so you can get it without re-calculating again. If you know every vector will need it's angles calculated multiple times, use the first method I wrote and cache it, i.e. v.angle = .... You can then you can do v2.angle - v1.angleto find angle between the two, etc.
i.e. have

编辑 2
如果您多次使用向量长度,要加快速度,请将其另存为 eg,v.length = ...以便您无需再次重新计算即可获得它。如果您知道每个向量都需要多次计算其角度,请使用我编写的第一种方法并将其缓存,即v.angle = .... 然后你可以v2.angle - v1.angle找到两者之间的角度等,
即有

function Vector(x, y){
    this.x = x;
    this.y = y;
    this.length = Math.sqrt(x*x + y*y);
    this.angle = Math.acos( x / this.length );
}


jsperfof pre-computing and finding in an array of 3601items vs using acosdirectly

jsperf的预计和在3601项目数组中查找vs直接使用acos

回答by Tommy

That's definitely going to be smaller than a call to atan2, since it's a square root and then a linear search through 3600 possibilities. Conversely many processors implement atan2 directly — it's FPATAN in Intel land.

这肯定会比调用 小atan2,因为它是一个平方根,然后是对 3600 种可能性的线性搜索。相反,许多处理器直接实现 atan2——它是英特尔领域的 FPATAN。