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https://github.com/mihakralj/QuanTAlib.git
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corrections
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+1
-51
@@ -1,25 +1,10 @@
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namespace QuanTAlib;
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/// <summary>
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/// Represents a Root Mean Squared Error calculator that measures the square root of the average
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/// of the squares of the differences between actual values and predicted values.
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/// </summary>
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/// <remarks>
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/// The Rmse class calculates the Root Mean Squared Error using a circular buffer
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/// to efficiently manage the data points within the specified period.
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/// </remarks>
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public class Rmse : AbstractBase
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{
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private readonly CircularBuffer _actualBuffer;
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private readonly CircularBuffer _predictedBuffer;
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/// <summary>
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/// Initializes a new instance of the Rmse class with the specified period.
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/// </summary>
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/// <param name="period">The period over which to calculate the Root Mean Squared Error.</param>
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/// <exception cref="ArgumentOutOfRangeException">
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/// Thrown when period is less than 1.
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/// </exception>
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public Rmse(int period)
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{
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if (period < 1)
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@@ -33,19 +18,12 @@ public class Rmse : AbstractBase
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Init();
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}
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/// <summary>
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/// Initializes a new instance of the Mape class with the specified source and period.
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/// </summary>
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/// <param name="source">The source object to subscribe to for value updates.</param>
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/// <param name="period">The period over which to calculate the Mean Absolute Percentage Error.</param>
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public Rmse(object source, int period) : this(period)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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/// <summary>
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/// Initializes the Rmse instance by clearing the buffers.
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/// </summary>
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public override void Init()
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{
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base.Init();
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@@ -53,10 +31,6 @@ public class Rmse : AbstractBase
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_predictedBuffer.Clear();
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}
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/// <summary>
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/// Manages the state of the Rmse instance based on whether new values are being processed.
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/// </summary>
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/// <param name="isNew">Indicates whether the current inputs are new values.</param>
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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@@ -66,17 +40,6 @@ public class Rmse : AbstractBase
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}
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}
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/// <summary>
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/// Performs the Root Mean Squared Error calculation for the current period.
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/// </summary>
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/// <returns>
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/// The calculated Root Mean Squared Error value for the current period.
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/// </returns>
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/// <remarks>
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/// This method calculates the Root Mean Squared Error using the formula:
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/// RMSE = sqrt(sum((actual - predicted)^2) / n)
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/// where actual is each actual value, predicted is each predicted value, and n is the number of values.
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/// </remarks>
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protected override double Calculation()
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{
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ManageState(Input.IsNew);
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@@ -106,17 +69,4 @@ public class Rmse : AbstractBase
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IsHot = _index >= WarmupPeriod;
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return rmse;
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}
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/// <summary>
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/// Calculates the Root Mean Squared Error for the given actual and predicted values.
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/// </summary>
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/// <param name="actual">The actual value.</param>
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/// <param name="predicted">The predicted value.</param>
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/// <returns>The calculated Root Mean Squared Error.</returns>
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public double Calc(double actual, double predicted)
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{
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Input = new TValue(DateTime.Now, actual);
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Input2 = new TValue(DateTime.Now, predicted);
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return Calculation();
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}
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}
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