mapv
Version:
a library of geography visualization
113 lines (91 loc) • 3.31 kB
HTML
<html>
<head>
<meta charset="UTF-8">
<title></title>
<style type="text/css">
html, body {
width: 100%;
height: 100%;
margin: 0;
padding: 0;
overflow: hidden;
}
#map {
width: 100%;
height: 100%;
}
</style>
</head>
<body>
<div id="map"></div>
<canvas id="canvas"></canvas>
<script type="text/javascript" src="http://apps.bdimg.com/libs/jquery/2.1.1/jquery.min.js"></script>
<script type="text/javascript" src="http://api.map.baidu.com/api?v=2.0&ak=1XjLLEhZhQNUzd93EjU5nOGQ"></script>
<script type="text/javascript" src="../build/mapv.js"></script>
<script type="text/javascript">
// 百度地图API功能
var map = new BMap.Map("map", {
enableMapClick: false
}); // 创建Map实例
map.centerAndZoom(new BMap.Point(105.403119, 38.028658), 5); // 初始化地图,设置中心点坐标和地图级别
map.enableScrollWheelZoom(true); // 开启鼠标滚轮缩放
map.setMapStyle({
styleJson: [
{
"featureType": "all",
"elementType": "all",
"stylers": {
"lightness": 61,
"saturation": -100
}
}
]
});
var randomCount = 500;
var data = [];
var citys = ["北京","天津","上海","重庆","石家庄","太原","呼和浩特","哈尔滨","长春","沈阳","济南","南京","合肥","杭州","南昌","福州","郑州","武汉","长沙","广州","南宁","西安","银川","兰州","西宁","乌鲁木齐","成都","贵阳","昆明","拉萨","海口"];
// 构造数据
while (randomCount--) {
var cityCenter = mapv.utilCityCenter.getCenterByCityName(citys[parseInt(Math.random() * citys.length)]);
data.push({
geometry: {
type: 'Point',
coordinates: [cityCenter.lng - 2 + Math.random() * 4, cityCenter.lat - 2 + Math.random() * 4]
},
count: parseInt(4 * Math.random())
});
}
var allDataSet = new mapv.DataSet(data);
var dataSet = new mapv.DataSet(data);
var options = {
splitList: {
other: 'white',
1: 'blue',
2: 'yellow',
3: 'red'
},
size: 2,
max: 30,
draw: 'category'
}
var mapvLayer = new mapv.baiduMapLayer(map, dataSet, options);
var legend = mapvLayer.getLegend();
legend.style.position = 'absolute';
legend.style.left = '10px';
legend.style.bottom = '50px';
document.body.appendChild(legend);
$(legend).delegate('div', 'click', function () {
var value = $(this).attr('value');
var data = allDataSet.get({
filter: function (item) {
if (item.count == value) {
return true;
}
}
});
dataSet.set(data);
});
</script>
</body>
</html>