【js类库Raphaël】使用raphael.js根据点坐标绘制平滑曲线

 一、可供参考的文档资料。

raphaeljs官网：http://raphaeljs.com/

w3c关于path的介绍：http://www.w3.org/TR/2003/REC-SVG11-20030114/paths.html

mdn关于path的介绍（英文版）：https://developer.mozilla.org/en-US/docs/Web/SVG/Tutorial/Paths

mdn关于path的介绍（中文版）：https://developer.mozilla.org/zh-CN/docs/Web/SVG/Tutorial/Paths

二、简介

raphaeljs目前支持的浏览器： Firefox 3.0+, Safari 3.0+, Chrome 5.0+, Opera 9.5+, Internet Explorer 6.0+.

因为支持ie6，所以应用可以更广泛些。

超级喜欢的一个demo：http://raphaeljs.com/polar-clock.html

三、实例

使用raphael.js根据点坐标绘制平滑曲线

难点：需要理解svg如何使用贝塞尔曲线；如何获得贝塞尔曲线的锚点坐标。

效果图：

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" alt="" width="378" height="152" />

代码：

<html>
<head>
        <meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
        <meta charset="utf-8">
        <title>Carl Test</title>
        <script src="./js/raphael.js"></script>
</head>
<body>
<div id="carl"></div>

<script>
window.onload = function () {

    //获取锚点
    function getAnchors(p1x, p1y, p2x, p2y, p3x, p3y) {
        var l1 = (p2x - p1x) / 2,
            l2 = (p3x - p2x) / 2,
            a = Math.atan((p2x - p1x) / Math.abs(p2y - p1y)),
            b = Math.atan((p3x - p2x) / Math.abs(p2y - p3y));
        a = p1y < p2y ? Math.PI - a : a;
        b = p3y < p2y ? Math.PI - b : b;
        var alpha = Math.PI / 2 - ((a + b) % (Math.PI * 2)) / 2,
            dx1 = l1 * Math.sin(alpha + a),
            dy1 = l1 * Math.cos(alpha + a),
            dx2 = l2 * Math.sin(alpha + b),
            dy2 = l2 * Math.cos(alpha + b);
        return {
            x1: p2x - dx1,
            y1: p2y + dy1,
            x2: p2x + dx2,
            y2: p2y + dy2
        };
    }

    (function(){
        var data = [{x:35,y:180},{x:125,y:59},{x:250,y:180},{x:450,y:70},{x:530,y:170}];
        var paper = Raphael("carl", 800, 300); 

        var p;
        for(var i=0, ii = data.length; i<data.length;i++){
            var point = data[i];
            var x = point.x;
            var y = point.y;
            if(!i){
                 p = ["M", x, y, "C", x, y];
            }
            if (i && i < ii - 1) {
               var point1 = data[i-1];
               var point2 = data[i+1];
                var a = getAnchors(point1.x, point1.y, x, y, point2.x, point2.y);//获取锚点
                p = p.concat([a.x1, a.y1, x, y, a.x2, a.y2]);

                paper.circle(a.x1, a.y1).attr({fill: "red",stroke:"#fff",r:3});//锚点
                paper.circle(a.x2, a.y2).attr({fill: "red",stroke:"#fff",r:3});//锚点
                paper.path('M'+a.x1+','+a.y1+' L'+x+','+y).attr({stroke:"red"});//锚点到点的连线
                paper.path('M'+a.x2+','+a.y2+' L'+x+','+y).attr({stroke:"red"});//锚点到点的连线
            }

            paper.circle(x,y).attr({fill: "#34C400",stroke:"#fff",r:3});

        }
        p = p.concat([x,y,x,y]);
        paper.path().attr({'path':p}).attr({stroke:"#34C400"});

    })();

};
</script>
</body>
</html>

查看：

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" 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" 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