你怎么能在RX做一个简单的,有状态变换序列的?
说,我们要做出的IObservable noisySequence的指数移动平均变换。
每当noisySequence蜱,emaSequence应剔和返回值(previousEmaSequenceValue *(1-拉姆达)+ latestNoisySequenceValue *波长)
我想我们使用的主题,但究竟怎么了?
公共静态无效的主要() { 变种兰特=新的随机(); 的IObservable<双>序列观测= .Interval(TimeSpan.FromMilliseconds(1000))。选择(价值=>价值+ rand.NextDouble()); Func键<双层,双> addNoise = X => X + 10 *(rand.NextDouble() - 0.5); 的IObservable<双> noisySequence = sequence.Select(addNoise); 受试对象;双> exponentialMovingAverage =新的受试对象;双>(); //? sequence.Subscribe(价值=> Console.WriteLine(原序+值)); noisySequence.Subscribe(价值=> Console.WriteLine(噪声序列+值)); exponentialMovingAverage.Subscribe(价值=> Console.WriteLine(EMA序+值)); 到Console.ReadLine(); }解决方案
这是你可以附加状态的序列。在这种情况下,计算出的最后10个值的平均值
VAR movingAvg = noisySequence.Scan(新名单<双>( ),(缓冲,值)=> { buffer.Add(价值); 如果(buffer.Count> MAXSIZE) { buffer.RemoveAt(0); } 返回缓冲区; })选择(缓冲=> buffer.Average());
但是,你可以使用窗口(其中缓冲区是有点泛化的),让你的平均了。
noisySequence.Window(10)。选择(窗口=> window.Average()) .SelectMany(averageSequence => averageSequence);
How can you do in RX a simple, stateful transform of a sequence?
Say we want to make an exponential moving average transform of a IObservable noisySequence.
Whenever noisySequence ticks, emaSequence should tick and return the value (previousEmaSequenceValue*(1-lambda) + latestNoisySequenceValue*lambda)
I guess we use Subjects, but how exactly?
public static void Main() { var rand = new Random(); IObservable<double> sequence = Observable .Interval(TimeSpan.FromMilliseconds(1000)) .Select(value => value + rand.NextDouble()); Func<double, double> addNoise = x => x + 10*(rand.NextDouble() - 0.5); IObservable<double> noisySequence = sequence.Select(addNoise); Subject<double> exponentialMovingAverage = new Subject<double>(); // ??? sequence.Subscribe(value => Console.WriteLine("original sequence "+value)); noisySequence.Subscribe(value => Console.WriteLine("noisy sequence " + value)); exponentialMovingAverage.Subscribe(value => Console.WriteLine("ema sequence " + value)); Console.ReadLine(); }解决方案
This is how you can attach state to a sequence. In this case it calculates the average of the last 10 values.
var movingAvg = noisySequence.Scan(new List<double>(), (buffer, value)=> { buffer.Add(value); if(buffer.Count>MaxSize) { buffer.RemoveAt(0); } return buffer; }).Select(buffer=>buffer.Average());But you could use Window (which Buffer is sort of a generalisation of) to get your average too.
noisySequence.Window(10) .Select(window=>window.Average()) .SelectMany(averageSequence=>averageSequence);
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RX:状态变换顺序,例如指数移动平均线
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