117 lines
4.9 KiB
MQL5
117 lines
4.9 KiB
MQL5
//+------------------------------------------------------------------+
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//| Inference.mq5 |
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//| Eugene |
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//| https://www.mql5.com |
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//+------------------------------------------------------------------+
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#property copyright "Eugene"
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#property link "https://www.mql5.com"
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#property version "1.00"
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#include <CategoricalHMM\CategoricalHMM.mqh>
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#include <Graphics\Graphic.mqh>
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//+------------------------------------------------------------------+
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//| Script program start function |
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//+------------------------------------------------------------------+
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void OnStart()
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{
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int n_states = 2; // Количество скрытых состояний
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int n_emissions = 6; // Количество возможных исходов (количество классов)
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// --- 1. Создаем модель (seed=99 для повторяемости) ---
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CCategoricalHMM model(n_states, n_emissions, 99);
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// --- Задаем параметры модели ---
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// --- 2. Матрица переходов TR ---
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matrix tr = {{0.95, 0.05},
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{0.1, 0.9}
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};
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// --- 3.Матрицу эмиссий (E) ---
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matrix e = {{1.0/6, 1.0/6, 1.0/6, 1.0/6, 1.0/6, 1.0/6},
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{0.1, 0.1, 0.1, 0.1, 0.1, 0.5}
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};
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// --- 4. Генерируем последовательность наблюдений и скрытых состояний ---
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vector y;
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vector z;
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int n_samples = 300; // Количество генерируемых выборок
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model.Sample(n_samples, tr, e, y, z);
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PrintFirst(z,"First 5 states",5); // First 5 states: [1 1 1 1 1]
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PrintFirst(y,"First 5 emissions",5); // First 5 emissions: [6 1 5 2 3]
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// --- БЛОК ВИЗУАЛИЗАЦИИ ---
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int plotLimit = 300; // Рисуем первые 300 точек
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double x[], y_[];
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ArrayResize(x, plotLimit);
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ArrayResize(y_, plotLimit);
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for(int i = 0; i < plotLimit; i++)
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{
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x[i] = i;
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y_[i] = z[i];
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}
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ChartSetInteger(0,CHART_SHOW,false);
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CGraphic graphic;
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ulong width = ChartGetInteger(0,CHART_WIDTH_IN_PIXELS);
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ulong height = ChartGetInteger(0,CHART_HEIGHT_IN_PIXELS);
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graphic.Create(0,"HMM_States_Plot",0,0,0,int(width),int(height));
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CCurve *curve = graphic.CurveAdd(x, y_, ColorToARGB(clrDodgerBlue, 255), CURVE_LINES,"States");
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curve.LinesStyle(STYLE_SOLID);
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curve.LinesWidth(2);
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graphic.BackgroundMainColor(ColorToARGB(clrBlack,255));
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graphic.BackgroundMainSize(24);
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graphic.BackgroundMain("States over time");
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graphic.XAxis().Name("Time");
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graphic.XAxis().NameSize(18);
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graphic.YAxis().Name("State (1=Fair, 2=Loaded)");
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graphic.YAxis().NameSize(18);
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graphic.YAxis().Min(1);
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graphic.YAxis().Max(2);
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graphic.CurvePlotAll();
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graphic.Update();
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Sleep(5*1000);
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ChartSetInteger(0,CHART_SHOW,true);
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graphic.Destroy();
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ChartRedraw(0);
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// --- Эмпирическая вероятность наблюдения=6 для симметричной(Fair) и смещенной (Loaded) кости ---
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PrintFormat("Empirical probability '6' (Fair): %.3f", CalculateSixFreq(y, z, 1));
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PrintFormat("Empirical probability '6' (Loaded): %.3f", CalculateSixFreq(y, z, 2));
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// --- Inference ---
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matrix Filtering, Smoothing, bs;
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double marginal_loglik;
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vector s;
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if(model.Inference(y,tr,e,Smoothing,marginal_loglik,Filtering,bs,s))
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{
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Print("---Inference---");
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PrintFormat("Логарифм правдоподобия (marginal_loglik): %.10f", marginal_loglik);
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Print("\nМатрица Smoothing (апостериорные вероятности):");
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PrintMatrixFormatted(Smoothing);
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Print("\nМатрица Filtering :");
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PrintMatrixFormatted(Filtering);
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}
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//MatrixToCSV("FilteringDist.csv",Filtering);
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//MatrixToCSV("SmoothingDist.csv",Smoothing);
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//VectorToCSV("TrueStates.csv", z);
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}
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//+------------------------------------------------------------------+
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//+-------------------------------------------------------------------+
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//|Возвращает частоту выпадения шестёрки | |
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//+-------------------------------------------------------------------+
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double CalculateSixFreq(const vector &r, const vector &s, int stateTarget)
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{
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int count = 0, total = 0;
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for(int i=0; i<(int)r.Size(); i++)
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{
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if(s[i] == stateTarget)
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{
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total++;
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if(r[i] == 6)
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count++;
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}
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}
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return (total > 0) ? (double)count/total : 0;
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}
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//+------------------------------------------------------------------+
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