94 lines
3.6 KiB
MQL5
94 lines
3.6 KiB
MQL5
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//+------------------------------------------------------------------+
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//| Learning.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;
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int n_emissions = 6;
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int n_samples = 300;
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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. Устанавливаем матрицу 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.Устанавливаем 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,z;
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model.Sample(n_samples, tr, e, y, z);
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// --- 5. Создаем новую модель и обучаем на сгенерированых данных ---
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CCategoricalHMM hmm(n_states, n_emissions);
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// --- В качестве начальных параметров зададим: ---
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matrix initialTR = {{0.7, 0.3},
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{0.3, 0.7}
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};
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matrix initialE = {{0.15, 0.05, 0.1, 0.1, 0.4, 0.2},
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{0.05, 0.15, 0.1, 0.1, 0.3, 0.3}
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};
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hmm.m_TR = initialTR;
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hmm.m_E = initialE;
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double tol = 1e-6;
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if(hmm.Fit(y,100, tol, true))
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{
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Print("\n--- Результаты ---");
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PrintFormat("Final LogLikelihood: %.6f", hmm.m_logliks[hmm.m_logliks.Size() - 1]);
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Print("Estimated TR:\n", hmm.m_TR);
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Print("True TR:\n", tr);
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Print("Estimated E:\n", hmm.m_E);
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Print("True E:\n", e);
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}
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// --- БЛОК ВИЗУАЛИЗАЦИИ ---
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int plotLimit = (int)hmm.m_logliks.Size();
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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] = hmm.m_logliks[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,"LL");
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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("EM Training Progress");
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graphic.XAxis().Name("Iteration");
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graphic.XAxis().NameSize(18);
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graphic.YAxis().Name("Log Likelihood");
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graphic.YAxis().NameSize(18);
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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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}
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//+------------------------------------------------------------------+
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