android - SciChart Android 实时绘图 : How to maximize graphing speed?

Question

我正在使用 Scichart for android 编写一个实时绘图应用程序。我一直在用

FastLineRenderableSeries 作为我的数据系列的包装器

但我想知道为了最大限度地提高绘图速度，Android SciChart 还存在哪些其他技术？

特别是当我使用 IXyDataSeries 并将 x 轴大小从 10,000 点增加到 100,000 点时，我特别注意到性能下降。在我将大约 90,000 个点添加到我的 IXyDataSeries 之前，绘图的速度一直保持很快。

谢谢大家。我是 stackoverflow 的新手……与其说是 CS 人员，不如说是 mechE。

这是我的 graphFragment 类，它以字符串形式接收 UDP 传感器数据，将其拼接并将其添加到 IXyDataSeries。

public class GraphFragment extends Fragment { 

    //Various fields...
    //UDP Settings
    private UdpClient client;
    private String hostname;
    private int remotePort;
    private int localPort;

    //Use to communicate with UDPDataClass
    private Handler handler;

    private boolean listenerExists = false;
    private int xBound = 100000; //**Graphing Slows if xBound is TOO large**
    private int yBound = 5000;
    private boolean applyBeenPressed = false;

    private GraphDataSource dataSource; //Gets data from UDPDataClass
    private SciChartSurface plotSurface; //Graphing Surface
    protected final SciChartBuilder sciChartBuilder = SciChartBuilder.instance();

    //Data Series containers
    //Perhaps it would be better to use XyySeries here?
    private final IXyDataSeries<Double, Double> dataSeriesSensor1 = sciChartBuilder.newXyDataSeries(Double.class, Double.class).build();
    private final IXyDataSeries<Double, Double> dataSeriesSensor2 = sciChartBuilder.newXyDataSeries(Double.class, Double.class).build();
    private final IXyDataSeries<Double, Double> dataSeriesSensor3 = sciChartBuilder.newXyDataSeries(Double.class, Double.class).build();
    private final IXyDataSeries<Double, Double> dataSeriesSensor4 = sciChartBuilder.newXyDataSeries(Double.class, Double.class).build();
    private final IXyDataSeries<Double, Double> dataSeriesSensor5 = sciChartBuilder.newXyDataSeries(Double.class, Double.class).build();
    private final IXyDataSeries<Double, Double> dataSeriesSensor6 = sciChartBuilder.newXyDataSeries(Double.class, Double.class).build();
    private ArrayList<IXyDataSeries<Double,Double>> dataSeriesList = new ArrayList<>(Arrays.asList(dataSeriesSensor1,dataSeriesSensor2,dataSeriesSensor3,dataSeriesSensor4, dataSeriesSensor5, dataSeriesSensor6));
    private ArrayList<Double> xCounters = new ArrayList<>(Arrays.asList(0.0,0.0,0.0,0.0,0.0,0.0));

    @Override
    public View onCreateView(LayoutInflater inflater, ViewGroup container, Bundle savedInstanceState) {
    final View frag = inflater.inflate(R.layout.graph_fragment, container, false);

    plotSurface = (SciChartSurface) frag.findViewById(R.id.dynamic_plot);

    dataSource = new GraphDataSource(); //Run the data handling on a separate thread
    dataSource.start();

    UpdateSuspender.using(plotSurface, new Runnable() {
        @Override
        public void run() {
            final NumericAxis xAxis = sciChartBuilder.newNumericAxis().withVisibleRange(0,xBound).build();
            final NumericAxis yAxis = sciChartBuilder.newNumericAxis().withVisibleRange(0,yBound).build();

            //These are wrappers for the series we will add the data to...It contains the formatting
            final FastLineRenderableSeries rs1 = sciChartBuilder.newLineSeries().withDataSeries(dataSeriesSensor1).withStrokeStyle(ColorUtil.argb(0xFF, 0x40, 0x83, 0xB7)).build(); //Light Blue Color
            final FastLineRenderableSeries rs2 = sciChartBuilder.newLineSeries().withDataSeries(dataSeriesSensor2).withStrokeStyle(ColorUtil.argb(0xFF, 0xFF, 0xA5, 0x00)).build(); //Light Pink Color
            final FastLineRenderableSeries rs3 = sciChartBuilder.newLineSeries().withDataSeries(dataSeriesSensor3).withStrokeStyle(ColorUtil.argb(0xFF, 0xE1, 0x32, 0x19)).build(); //Orange Red Color
            final FastLineRenderableSeries rs4 = sciChartBuilder.newLineSeries().withDataSeries(dataSeriesSensor4).withStrokeStyle(ColorUtil.argb(0xFF, 0xFF, 0xFF, 0xFF)).build(); //White color
            final FastLineRenderableSeries rs5 = sciChartBuilder.newLineSeries().withDataSeries(dataSeriesSensor5).withStrokeStyle(ColorUtil.argb(0xFF, 0xFF, 0xFF, 0x99)).build(); //Light Yellow color
            final FastLineRenderableSeries rs6 = sciChartBuilder.newLineSeries().withDataSeries(dataSeriesSensor6).withStrokeStyle(ColorUtil.argb(0xFF, 0xFF, 0x99, 0x33)).build(); //Light Orange color

            Collections.addAll(plotSurface.getXAxes(), xAxis);
            Collections.addAll(plotSurface.getYAxes(), yAxis);
            Collections.addAll(plotSurface.getRenderableSeries(), rs1, rs2, rs3, rs4, rs5, rs6);
        }
    });

    return frag;
    }

 //This class receives the UDP sensor data as messages to its handler
 //Then it splices the data
 //Adds the data to the IXySeries
 //Then the UpdateSuspender updates the graph
 //New data arrives approx every 50 ms (around 20x a second)
 //Graphing slows when xAxis is increased to ~100,000
 //X data is only counters...Only care about Y data
 public class GraphDataSource extends Thread{

    public void run(){
        Looper.prepare();
        //Get Data from UDP Data Class when its available
        handler = new Handler(){
            public void handleMessage(Message msg){
                String sensorData = msg.getData().getString("data"); //Data receiveds
                if(dataValid(sensorData)){
                    sensorData = sensorData.replaceAll("\\s", "");
                    final String[] dataSplit = sensorData.split(","); //split the data at the commas

                    UpdateSuspender.using(plotSurface, new Runnable() {    //This updater graphs the values
                            @Override
                            public void run() {
                                spliceDataAndAddData(dataSplit);
                            }
                        });
                }
            }
        };
        Looper.loop();
    }

    /**
     *
     * @param data string of the udp data
     * @return true if the data isn't corrupted..aka the correct length
     */
    private boolean dataValid(String data){
        return ((data.length() == 1350));
    }

    /**
     *
     * @param dataSplit String[] of the entire data
     *  Adds the each sensor data to the IXySeries representing the data
     */
    private void spliceDataAndAddData(String[] dataSplit){
        addToSensorSeries(dataSplit, 1);
        addToSensorSeries(dataSplit, 2);
        addToSensorSeries(dataSplit, 3);
        addToSensorSeries(dataSplit, 4);
        addToSensorSeries(dataSplit, 5);
        addToSensorSeries(dataSplit, 6);
    }

    /**
     *
     * @param dataSplit data to split into individual sensor array
     *                  must contain only string representations of numbers
     * @param sensorSeriesNumber which sensors to collect the data points of
     * Adds the data to the corresponding IXySeries 
     */
    private void addToSensorSeries(String[] dataSplit, int sensorSeriesNumber){
        sensorSeriesNumber -= 1;  //Adds each value individually to the series
        double xcounter = xCounters.get(sensorSeriesNumber);
        int i = sensorSeriesNumber;
        int dataSize = dataSplit.length - 1;
        String num = "";
        while(true){
            if(i < 6){ //This is the base case...add the first set of data
                num = dataSplit[i];
                try {
                    if(xcounter > xBound){
                        xcounter = 0;
                        dataSeriesList.get(sensorSeriesNumber).clear();
                    }
                    dataSeriesList.get(sensorSeriesNumber).append(xcounter, Double.parseDouble(num)); //appends every number...
                }catch (Exception e){
                    //Corrupt data
                }
            }else if((i) <= dataSize && i >= 6){ //Will start to get hit after the second time
                num = dataSplit[i];
                try {
                    if(xcounter > xBound){
                        xcounter = 0;
                        dataSeriesList.get(sensorSeriesNumber).clear();
                    }
                    dataSeriesList.get(sensorSeriesNumber).append(xcounter, Double.parseDouble(num));
                }catch (Exception e){
                    //Corrupt data
                }
            }else{
                break;
            }
            xcounter++;
            i += 6;
        }
        xCounters.set(sensorSeriesNumber,xcounter);
    }
}

Answer 1

我查看了您的代码，但不确定我们是否可以对此做些什么。您的示例包含 6 个 XyDataSeries，XRange 从 0 到 100000，这在屏幕上给出了 600 000 个点，这对于 HTC One 上的实时示例来说非常好。在 SciChart 性能演示中，您可以看到仅使用 3 个 XyDataSeries 实例，这允许在每个系列中绘制更多点

披露:我是 SciChart Android 团队的首席开发人员

---

但我认为您可以通过在代码中添加一些优化来获得额外的 FPS。实时图表的主要问题在于更新图表的代码——它经常被调用，所以如果你在更新期间创建了一些对象并且不保存它，那么这可能会导致问题，因为 Android 中的 GC(GC 传递很慢而且它可以在 GC 收集所有未使用的对象时暂停所有应用程序的线程)。所以我建议你接下来做:

• 我建议增加 heap size在您的应用程序中:如果您有效地使用内存，应用程序将拥有更多内存 - 执行的 GC 将更少。
• 尝试减少装箱/拆箱的数量，并在频繁调用的代码(例如数据系列更新)中分配较少的对象。基本上，您需要忘记在更新数据系列的回调中创建任何对象。在您的代码中，我注意到很少有地方发生装箱/拆箱。此代码每秒调用一次，并且在循环中调用一些方法，因此装箱/拆箱的效果会显着影响应用程序的性能:

dataSeriesList.get(sensorSeriesNumber).append(xcounter, Double.parseDouble(num));

double xcounter = xCounters.get(sensorSeriesNumber);

xCounters.set(sensorSeriesNumber,xcounter);

我建议您使用 append override它接受 IValues。当您非常频繁地附加大量数据时，使用接受 IValue 的附加可以避免对基本类型进行不必要的装箱/拆箱。

• 此外，除非您在创建 XyDataSeries 时确实需要 Double，否则我建议使用 Float 或 Integer。这有可能将内存消耗减少一半(8 个字节用于存储 double 与 4 个字节用于存储 int/float)，因此应用程序有更多可用内存，从而可以降低执行 GC 的频率。

希望对您有所帮助。