/// <summary>
/// 新增加一个数据判断通过后才入库。
/// 添加成功后返回true。
/// </summary>
/// <param name="key"></param>
public virtual Boolean CheckAndAdd(double newVal, NumeralWindowData buffer)
{
if (ErrorJudge.IsFirst)
{
ErrorJudge.SetReferenceValue(newVal);
}
else
{
ErrorJudge.SetReferenceValue(this.CurrentValue);
}
if (ErrorJudge.IsOverLimit(newVal))//判断是否超限
{
var list = buffer.ToList();
list.Insert(0, newVal);
NumeralWindowData newBuffer = new NumeralWindowData(list);
if (ErrorJudge.IsJumped(buffer)) //跳跃，则重新计算整数值，否则认为是粗差，直接忽略。
{
CurrentAdjustment = null; //重新计算滤波值，
Add(newVal);
return(true);
}
return(false);
}
else
{
Add(newVal);
return(true);
}
}
/// <summary>
/// 获取数窗口
/// </summary>
/// <param name="refKey"></param>
/// <returns></returns>
public NumeralWindowData <TKey> GetNumeralWindowData(TKey refKey)
{
foreach (var item in Cashes.Data)
{
if (item.Key.Contains(refKey))
{
return(Cashes[item.Key]);
}
}
//提取数据
NumeralWindowData <TKey> window = new NumeralWindowData <TKey>(int.MaxValue);
var seg = this.GetSegmentKeyValue(refKey);
if (seg.Value == null)
{
return(null);
}
foreach (var item in seg.Value.Data)
{
window.Add(item.Key, item.Value);
}
//缓存
Cashes[seg.Key] = window;
return(window);
}
/// <summary>
/// 判断是否是跳变。通过后续缓存窗口数据判断。
/// 请先调用 IsOverTolerance 确定超限后，再调用我。
/// 这里假定粗差只出现少数几次或1次。
/// </summary>
/// <param name="buffer"></param>
/// <returns></returns>
public bool IsJumped(IEnumerable <double> buffer)
{
//算法：如果缓存中下面几个全超限，则认为不是粗差，是跳变。
var nextFive = new NumeralWindowData(buffer);
return(IsOverLimit(nextFive.AverageValue));
}
public static NumeralWindowData operator +(NumeralWindowData data, double val)
{
NumeralWindowData result = new NumeralWindowData(data.Count);
foreach (var item in data)
{
result.Add(item + val);
}
return(result);
}
/// <summary>
/// 获取差分指定次的数据窗口结果，后减前
/// </summary>
/// <returns></returns>
public NumeralWindowData <TKey> GetDifferWindow(int differCount)
{
NumeralWindowData <TKey> result = this;
for (int i = 0; i < differCount; i++)
{
result = result.GetDifferWindow();
}
return(result);
}
public static NumeralWindowData <TKey> operator +(NumeralWindowData <TKey> data, double val)
{
NumeralWindowData <TKey> result = new NumeralWindowData <TKey>(data.Count);
foreach (var item in data.Data)
{
result.Add(item.Key, item.Value + val);
}
return(result);
}
/// <summary>
/// 获取差分一次的数据窗口结果。
/// </summary>
/// <returns></returns>
public NumeralWindowData GetDifferWindow()
{
double[] differs = new double[WindowSize - 1];
for (int i = 0; i < WindowSize - 1; i++)
{
differs[i] = this[i + 1] - this[i];
}
NumeralWindowData differWindow = new NumeralWindowData(differs);
return(differWindow);
}
/// <summary>
/// 计算整数偏差。新偏差与原数据应该控制在 0.5 以内。
/// </summary>
/// <param name="buffer"></param>
/// <returns></returns>
public int CaculateIntBias(NumeralWindowData buffer)
{
var average = buffer.AverageValue;
var newIntBias = Geo.Utils.DoubleUtil.GetNearstIntBias(average, this.CurrentValue);
if (IntBias != newIntBias)
{
OnIntBiasChanged(newIntBias);
}
return(newIntBias);
}
/// <summary>
/// 判断是否是跳变。通过后续缓存窗口数据判断。
/// 请先调用 IsOverTolerance 确定超限后，再调用我。
/// 这里假定粗差只出现少数几次或1次。
/// </summary>
/// <param name="buffer"></param>
/// <param name="referValue"></param>
/// <returns></returns>
public bool IsJumped(IEnumerable <double> buffer, double referValue)
{
if (buffer == null)
{
return(false);
}
//算法：如果缓存中下面几个全超限，则认为不是粗差，是跳变。
var nextFive = new NumeralWindowData(buffer);
return(IsOverLimit(nextFive.AverageValue, referValue));
}
/// <summary>
/// 拟合后返回各项的拟合误差
/// </summary>
/// <param name="polyFitOrder"></param>
/// <returns></returns>
public NumeralWindowData <TKey> GetFitErrorWindow(int polyFitOrder)
{
NumeralWindowData <TKey> errors = new NumeralWindowData <TKey>(this.WindowSize)
{
KeyToDouble = KeyToDouble
};
var fitter = BuildPolyfitter(polyFitOrder);
var firstKey = this.TheVeryFirstKey;
foreach (var item in this.OrderedData)
{
var x = KeyToDouble(item.Key) - KeyToDouble(firstKey);
var error = item.Value - fitter.GetY(x);
errors.Add(item.Key, error);
}
return(errors);
}
/// <summary>
/// 按键间隔分离小窗口。如果间之间的间距超过了指定宽度，则分离成两个或多个子窗口。
/// </summary>
/// <param name="funcKeyToDouble">将Key转换为数值</param>
/// <param name="maxKeySpan"></param>
/// <returns></returns>
public List <NumeralWindowData <TKey> > Split(Func <TKey, double> funcKeyToDouble, double maxKeySpan)
{
var initSelects = new List <NumeralWindowData <TKey> >();
var window = new NumeralWindowData <TKey>(Int16.MaxValue);
initSelects.Add(window);
var lastKeyVal = Double.MinValue;
foreach (var kv in this.Data)
{
var key = kv.Key;
var val = kv.Value;
var keVal = funcKeyToDouble(kv.Key);
if (window.Count < 1)
{
window.Add(kv.Key, kv.Value); lastKeyVal = keVal; continue;
}
var differ = Math.Abs(lastKeyVal - keVal);
var isPassed = differ <= maxKeySpan;
if (isPassed)
{
window.Add(kv.Key, kv.Value);
}
else
{
//update window size
window.WindowSize = window.Count;
//create new
window = new NumeralWindowData <TKey>(Int16.MaxValue);
initSelects.Add(window);
}
//update
lastKeyVal = keVal;
}
window.WindowSize = window.Count;
return(initSelects);
}
/// <summary>
/// 采用平均值方法，对值进行比较，如果超限则就地分解。
/// </summary>
/// <param name="errorTimes"></param>
/// <returns></returns>
public List <NumeralWindowData <TKey> > SplitByAverage(int errorTimes)
{
//1.初选，采用平均法，放大方差要求，将数据进行分段。
//遍历，
var initSelects = new List <NumeralWindowData <TKey> >();
var window = new NumeralWindowData <TKey>(Int16.MaxValue);
initSelects.Add(window);
foreach (var kv in this.Data)
{
var key = kv.Key;
var val = kv.Value;
if (window.Count < 1)
{
window.Add(kv.Key, kv.Value); continue;
}
var ave = window.Average;
var differ = Math.Abs(ave.Value - kv.Value);
var rms = ave.Rms == 0 ? double.MaxValue : ave.Rms;
var errorThreshold = errorTimes * rms;
var isPassed = differ <= errorThreshold;
if (isPassed)
{
window.Add(kv.Key, kv.Value);
}
else
{
window.WindowSize = window.Count;
window = new NumeralWindowData <TKey>(Int16.MaxValue);
initSelects.Add(window);
}
}
window.WindowSize = window.Count;
return(initSelects);
}
/// <summary>
/// 按照指定长度截断。最后如果太小，则直接追加到上一个。
/// </summary>
/// <param name="aboutSize">大致大小</param>
/// <returns></returns>
private List <NumeralWindowData <TKey> > Split(int aboutSize)
{
if (this.Count <= aboutSize)
{
return(new List <NumeralWindowData <TKey> >()
{
this
});
}
var initSelects = new List <NumeralWindowData <TKey> >();
var window = new NumeralWindowData <TKey>(aboutSize);
foreach (var kv in this.Data)
{
if (window.IsFull)
{
initSelects.Add(window);
window = new NumeralWindowData <TKey>(aboutSize);
}
window.Add(kv.Key, kv.Value);
}
//检查，最后如果太小，则直接追加到上一个。
if (window.Count < aboutSize / 2)
{
var last = initSelects.Last();
last.WindowSize += window.Count;
last.Add(window.Data);
}
else
{
initSelects.Add(window);
}
return(initSelects);
}
/// <summary>
/// 新增加一个数据判断通过后才入库。
/// 添加成功后返回true。
/// </summary>
/// <param name="key"></param>
public override Boolean CheckAndAdd(double newVal, NumeralWindowData buffer)
{
//这里同父类一样，采用原始数据判断，以减少计算量。
if (ErrorJudge.IsFirst) // 第一次取其小数
{
IntBias = CaculateIntBias(buffer.GetNeatlyWindowData());
ErrorJudge.SetReferenceValue(newVal);
}
else
{
ErrorJudge.SetReferenceValue(this.IntFraction.Value);
}
var fraction = newVal - IntBias;
if (ErrorJudge.IsOverLimit(newVal))//判断是否超限
{
var list = buffer.InsertAndReturnNew(0, newVal);
if (ErrorJudge.IsJumped(list))//跳跃，则重新计算整数值，否则认为是粗差，直接忽略。
{
var newBuffer2 = new NumeralWindowData(list);
var biasBuffer = newBuffer2.GetNeatlyWindowData();
IntBias = CaculateIntBias(biasBuffer);
fraction = newVal - IntBias;
Add(fraction);
return(true);
}
return(false);
}
else
{
Add(fraction);
return(true);
}
}
/// <summary>
/// 设置缓存。
/// </summary>
/// <param name="Buffers"></param>
/// <returns></returns>
public CyclicalNumerFilter SetBuffer(NumeralWindowData Buffers)
{
this.Buffers = Buffers;
return(this);
}
