如何使用D3/Rickshaw在时间序列图上标记离散点？

Question

我正在使用人力车创建一个实时更新的时间序列图.

这是演示:http://abhshkdz.github.io/icuvisualanalytics/prototypes/rickshaw.html

数据采用csv格式(时间,值),这是可视化的核心javascript:

var count = 0, index=0;

var margin  =   {top: 10, right: 10, bottom: 10, left: 10},
    width   =   window.innerWidth - margin.right - margin.left - 100,
    height  =   window.innerHeight - margin.top - margin.bottom - 100;

var graph = new Rickshaw.Graph( {
    element: document.querySelector("#chart"),
    width: width,
    height: height,
    renderer: 'line',
    min: -300,
    max: 500,
    preserve: true,
    series: new Rickshaw.Series.FixedDuration(
        [
            {
                name: 'ECG',
                color: palette.color()
            }
        ], 
        undefined,
        {
            timeInterval: 12.5,
            maxDataPoints: 400,
            timeBase: data[index][count].x
        })
    })

var x_axis = new Rickshaw.Graph.Axis.Time( { graph: graph } );

var y_axis = new Rickshaw.Graph.Axis.Y( {
        graph: graph,
        orientation: 'left',
        tickFormat: Rickshaw.Fixtures.Number.formatKMBT,
        element: document.getElementById('y_axis')
} );

var hoverDetail = new Rickshaw.Graph.HoverDetail( {
    graph: graph
} );

graph.render();

setInterval(function () {

    if (count == 2397) {
        count = 0;
        index++;
    }
    var d = {'ECG': data[index][count+=3].y};
    graph.series.addData(d);
    graph.render();

}, 12.5);

现在有另一组数据由算法生成.该数据也采用csv格式(时间,价值).它基本上找到了这个图的高峰.使用该数据,我想在此可视化本身上标记这些点.

据我所知,人力车本身并不支持使用不同渲染器的多个系列(两者都必须是直线或两个散点图等).

那我该怎么办呢？

Answer 1

多渲染器功能是大约一个月前添加的。此示例展示了如何在一个图表中组合多个渲染器。示例的相关代码：

var graph = new Rickshaw.Graph( {
    element: document.getElementById("chart"),
    renderer: 'multi',
    width: 900,
    height: 500,
    dotSize: 2,
    series: [
        {
            name: 'temperature',
            data: seriesData.shift(),
            color: 'rgba(255, 0, 0, 0.4)',
            renderer: 'stack'
        }, {
            name: 'heat index',
            data: seriesData.shift(),
            color: 'rgba(255, 127, 0, 0.4)',
            renderer: 'stack'
        }, {
            name: 'dewpoint',
            data: seriesData.shift(),
            color: 'rgba(127, 0, 0, 0.3)',
            renderer: 'scatterplot'
        }, {
            name: 'pop',
            data: seriesData.shift().map(function(d) { return { x: d.x, y: d.y / 4 } }),
            color: 'rgba(0, 0, 127, 0.4)',
            renderer: 'bar'
        }, {
            name: 'humidity',
            data: seriesData.shift().map(function(d) { return { x: d.x, y: d.y * 1.5 } }),
            renderer: 'line',
            color: 'rgba(0, 0, 127, 0.25)'
        }
    ]
});