#2 -- complete additive trent and seasonality

src/main/java/ru/ulstu/controllers/TimeSeriesController.java

@@ -10,7 +10,6 @@ import org.springframework.web.bind.annotation.RequestMapping;
 import org.springframework.web.bind.annotation.RequestParam;
 import org.springframework.web.bind.annotation.RestController;
 import ru.ulstu.configurations.ApiConfiguration;
-import ru.ulstu.models.Forecast;
 import ru.ulstu.models.ForecastParams;
 import ru.ulstu.models.TimeSeries;
 import ru.ulstu.models.exceptions.ModelingException;
@@ -52,7 +51,7 @@ public class TimeSeriesController {
 
     @PostMapping("getForecast")
     @ApiOperation("Получить прогноз временного ряда")
-    public ResponseEntity<Forecast> getForecastTimeSeries(@RequestBody ForecastParams forecastParams) throws ModelingException {
+    public ResponseEntity<TimeSeries> getForecastTimeSeries(@RequestBody ForecastParams forecastParams) throws ModelingException {
         return new ResponseEntity<>(timeSeriesService.getForecast(forecastParams.getOriginalTimeSeries(),
                 forecastParams.getCountForecast()), HttpStatus.OK);
     }

src/main/java/ru/ulstu/models/Forecast.java

@@ -1,31 +0,0 @@
-package ru.ulstu.models;
-
-public class Forecast {
-    private Model model;
-    private TimeSeries forecast;
-
-    public Forecast(Model model) {
-        this.model = model;
-        this.forecast = new TimeSeries("Forecast time series of '" + model.getOriginalTimeSeries().getName() + "'");
-    }
-
-    public Model getModel() {
-        return model;
-    }
-
-    public TimeSeries getForecastTimeSeries() {
-        return forecast;
-    }
-
-    public void addValue(TimeSeriesValue timeSeriesValue) {
-        forecast.addValue(timeSeriesValue);
-    }
-
-    @Override
-    public String toString() {
-        return "Forecast{" +
-                "model=" + model +
-                ", forecast=" + forecast +
-                '}';
-    }
-}

src/main/java/ru/ulstu/models/Model.java

@@ -1,27 +0,0 @@
-package ru.ulstu.models;
-
-public class Model {
-    private TimeSeries originalTimeSeries;
-    private TimeSeries modelTimeSeries;
-
-    public Model(TimeSeries originalTimeSeries) {
-        this.originalTimeSeries = originalTimeSeries;
-        this.modelTimeSeries = new TimeSeries("Model time series of '" + originalTimeSeries.getName() + "'");
-    }
-
-    public TimeSeries getOriginalTimeSeries() {
-        return originalTimeSeries;
-    }
-
-    public TimeSeries getModelTimeSeries() {
-        return modelTimeSeries;
-    }
-
-    public void addValue(TimeSeriesValue timeSeriesValue) {
-        modelTimeSeries.addValue(timeSeriesValue);
-    }
-
-    public void addValue(TimeSeriesValue basedOnValue, double value) {
-        modelTimeSeries.getValues().add(new TimeSeriesValue(basedOnValue.getDate(), value));
-    }
-}

src/main/java/ru/ulstu/models/TimeSeries.java

@@ -53,7 +53,7 @@ public class TimeSeries {
     }
 
     public void addValue(TimeSeriesValue basedOnValue, Double value) {
-        values.add(new TimeSeriesValue(basedOnValue.getDate().plusDays(1), value));
+        values.add(new TimeSeriesValue(basedOnValue.getDate(), value));
     }
 
     public TimeSeriesValue getLastValue() {

src/main/java/ru/ulstu/pages/IndexView.java

@@ -48,7 +48,7 @@ public class IndexView implements Serializable {
         LineChartSeries series2 = new LineChartSeries();
         series2.setLabel("Сглаженный ряд");
         try {
-            for (TimeSeriesValue value : timeSeriesService.getForecast(timeSeries, 10).getModel().getModelTimeSeries().getValues()) {
+            for (TimeSeriesValue value : timeSeriesService.smoothTimeSeries(timeSeries).getValues()) {
                 series2.set(DateTimeFormatter.ISO_LOCAL_DATE.format(value.getDate()), value.getValue());
             }
         } catch (ModelingException ex) {
@@ -59,7 +59,7 @@ public class IndexView implements Serializable {
         LineChartSeries series3 = new LineChartSeries();
         series3.setLabel("Прогноз");
         try {
-            for (TimeSeriesValue value : timeSeriesService.getForecast(timeSeries, 10).getForecastTimeSeries().getValues()) {
+            for (TimeSeriesValue value : timeSeriesService.getForecast(timeSeries, 5).getValues()) {
                 series3.set(DateTimeFormatter.ISO_LOCAL_DATE.format(value.getDate()), value.getValue());
             }
         } catch (ModelingException ex) {

src/main/java/ru/ulstu/services/TimeSeriesService.java

@@ -4,19 +4,20 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.stereotype.Service;
 import ru.ulstu.TimeSeriesUtils;
-import ru.ulstu.models.Forecast;
 import ru.ulstu.models.TimeSeries;
 import ru.ulstu.models.TimeSeriesValue;
 import ru.ulstu.models.exceptions.ModelingException;
+import ru.ulstu.tsMethods.exponential.AddTrendNoSeason;
 import ru.ulstu.tsMethods.exponential.ExponentialMethodParams;
-import ru.ulstu.tsMethods.exponential.ExponentialParamName;
-import ru.ulstu.tsMethods.exponential.NoTrendNoSeason;
 
 import java.time.LocalDateTime;
 import java.util.Arrays;
 import java.util.List;
 import java.util.stream.Collectors;
 
+import static ru.ulstu.tsMethods.exponential.ExponentialParamName.ALPHA;
+import static ru.ulstu.tsMethods.exponential.ExponentialParamName.BETA;
+
 
 @Service
 public class TimeSeriesService {
@@ -32,9 +33,16 @@ public class TimeSeriesService {
         return ts;
     }
 
-    public Forecast getForecast(TimeSeries timeSeries, int countPoints) throws ModelingException {
+    public TimeSeries getForecast(TimeSeries timeSeries, int countPoints) throws ModelingException {
-        NoTrendNoSeason nn = new NoTrendNoSeason(ExponentialMethodParams.of(ExponentialParamName.ALPHA, 0.8));
+        //NoTrendNoSeason nn = new NoTrendNoSeason(ExponentialMethodParams.of(ExponentialParamName.ALPHA, 0.8));
-        return nn.getForecast(timeSeries, countPoints);
+        AddTrendNoSeason an = new AddTrendNoSeason(timeSeries, ExponentialMethodParams.of(ALPHA, 0.8, BETA, 0.8));
+        return an.getForecast(countPoints);
+    }
+
+    public TimeSeries smoothTimeSeries(TimeSeries timeSeries) throws ModelingException {
+        //NoTrendNoSeason nn = new NoTrendNoSeason(timeSeries, ExponentialMethodParams.of(ExponentialParamName.ALPHA, 0.8));
+        AddTrendNoSeason an = new AddTrendNoSeason(timeSeries, ExponentialMethodParams.of(ALPHA, 0.8, BETA, 0.8));
+        return an.getModel();
     }
 
     public TimeSeries getTimeSeriesFromString(String tsString) {

src/main/java/ru/ulstu/tsMethods/TimeSeriesMethod.java

@@ -1,8 +1,6 @@
 package ru.ulstu.tsMethods;
 
 import ru.ulstu.TimeSeriesUtils;
-import ru.ulstu.models.Forecast;
-import ru.ulstu.models.Model;
 import ru.ulstu.models.TimeSeries;
 import ru.ulstu.models.TimeSeriesValue;
 import ru.ulstu.models.exceptions.ForecastValidateException;
@@ -15,44 +13,44 @@ import java.time.temporal.ChronoUnit;
  * Наиболее общая логика моделировани и прогнозирования временных рядов
  */
 public abstract class TimeSeriesMethod {
+    protected TimeSeries originalTimeSeries;
+    private TimeSeries model;
+
+    public TimeSeriesMethod(TimeSeries originalTimeSeries) throws ModelingException {
+        this.originalTimeSeries = originalTimeSeries;
+    }
+
     /**
      * Возвращает модельное представление временного ряда: для тех же точек времени что и в параметре timeSeries
      * строится модель. Количество точек может быть изменено: сокращено при сжатии ряда, увеличено при интерполяции.
      * Метод является шаблонным, выполняет операции валидации исходного ряда и потом его моделирование
      *
-     * @param timeSeries исходный временной ряд подлежащий моделированию
      * @return модель временного ряда
      * @throws TimeSeriesValidateException
      */
-    public Model getModel(TimeSeries timeSeries) throws ModelingException {
+    protected void makeModel() throws ModelingException {
-        validateTimeSeries(timeSeries);
+        validateTimeSeries();
-        return getModelOfValidTimeSeries(timeSeries);
+        model = getModelOfValidTimeSeries();
     }
 
     /**
      * Возвращает модельное представление валидного временного ряда: для тех же точек времени что и в параметре timeSeries
      * строится модель. Количество точек может быть изменено: сокращено при сжатии ряда, увеличено при интерполяции.
      *
-     * @param timeSeries исходный временной ряд подлежащий моделированию
      * @return
      */
-    protected abstract Model getModelOfValidTimeSeries(TimeSeries timeSeries) throws ModelingException;
+    protected abstract TimeSeries getModelOfValidTimeSeries() throws ModelingException;
 
     /**
      * Выполняет построение прогноза временного ряда. Даты спрогнозированных точек будут сгенерированы по модельным точкам.
      *
-     * @param model       модель временного ряда
      * @param countPoints количество точек для прогнозирования
      * @return прогноз временного ряда
      */
-    public Forecast getForecast(Model model, int countPoints) throws ModelingException {
+    public TimeSeries getForecastWithValidParams(int countPoints) throws ModelingException {
-        Forecast forecast = new Forecast(model);
+        TimeSeries forecast = generateEmptyForecastPoints(originalTimeSeries, countPoints);
-        forecast = generateEmptyForecastPoints(forecast, countPoints);
+        forecast.getFirstValue().setValue(getModel().getLastValue().getValue());
         forecast = makeForecast(forecast);
-        if (!forecast.getForecastTimeSeries().getFirstValue()
-                .equals(forecast.getModel().getModelTimeSeries().getLastValue())) {
-            throw new ForecastValidateException("Первая точка прогноза должна совпадать с последней модельной точкой");
-        }
         return forecast;
     }
 
@@ -62,15 +60,14 @@ public abstract class TimeSeriesMethod {
      * @param forecast Заготовка прогноза временного ряда с пустыми значениями
      * @return
      */
-    protected abstract Forecast makeForecast(Forecast forecast);
+    protected abstract TimeSeries makeForecast(TimeSeries forecast) throws ModelingException;
 
-    protected Forecast generateEmptyForecastPoints(Forecast forecast, int countPointForecast) {
+    protected TimeSeries generateEmptyForecastPoints(TimeSeries modelTimeSeries, int countPointForecast) {
-        long diffMilliseconds = TimeSeriesUtils.getTimeDifferenceInMilliseconds(forecast.getModel().getOriginalTimeSeries());
+        long diffMilliseconds = TimeSeriesUtils.getTimeDifferenceInMilliseconds(originalTimeSeries);
-        forecast.getForecastTimeSeries()
+        TimeSeries forecast = new TimeSeries("Forecast of " + originalTimeSeries.getName());
-                .addValue(new TimeSeriesValue(forecast.getModel().getModelTimeSeries().getLastValue().getDate()));
+        forecast.addValue(new TimeSeriesValue(modelTimeSeries.getLastValue().getDate()));
         for (int i = 1; i < countPointForecast + 1; i++) {
-            forecast.getForecastTimeSeries()
+            forecast.addValue(new TimeSeriesValue(forecast.getValues().get(i - 1).getDate().plus(diffMilliseconds, ChronoUnit.MILLIS)));
-                    .addValue(new TimeSeriesValue(forecast.getForecastTimeSeries().getValues().get(i - 1).getDate().plus(diffMilliseconds, ChronoUnit.MILLIS)));
         }
         return forecast;
     }
@@ -79,13 +76,12 @@ public abstract class TimeSeriesMethod {
      * Выполняет построение модели и прогноза временного ряда. Даты спрогнозированных точек будут сгенерированы
      * по модельным точкам.
      *
-     * @param timeSeries  временной ряда
      * @param countPoints количество точек для прогнозирования
      * @return прогноз временного ряда
      */
-    public Forecast getForecast(TimeSeries timeSeries, int countPoints) throws ModelingException {
+    public TimeSeries getForecast(int countPoints) throws ModelingException {
         validateForecastParams(countPoints);
-        return getForecast(getModel(timeSeries), countPoints);
+        return getForecastWithValidParams(countPoints);
     }
 
     private void validateForecastParams(int countPoints) throws ForecastValidateException {
@@ -94,18 +90,25 @@ public abstract class TimeSeriesMethod {
         }
     }
 
-    private void validateTimeSeries(TimeSeries timeSeries) throws TimeSeriesValidateException {
+    private void validateTimeSeries() throws TimeSeriesValidateException {
-        if (timeSeries == null || timeSeries.isEmpty()) {
+        if (originalTimeSeries == null || originalTimeSeries.isEmpty()) {
             throw new TimeSeriesValidateException("Временной ряд должен быть не пустым");
         }
-        if (timeSeries.getLength() < 2) {
+        if (originalTimeSeries.getLength() < 2) {
             throw new TimeSeriesValidateException("Временной ряд должен содержать хотя бы 2 точки");
         }
-        if (timeSeries.getValues().stream().anyMatch(val -> val == null || val.getValue() == null)) {
+        if (originalTimeSeries.getValues().stream().anyMatch(val -> val == null || val.getValue() == null)) {
             throw new TimeSeriesValidateException("Временной ряд содержит пустые значения");
         }
-        if (timeSeries.getValues().stream().anyMatch(val -> val.getDate() == null)) {
+        if (originalTimeSeries.getValues().stream().anyMatch(val -> val.getDate() == null)) {
             throw new TimeSeriesValidateException("Временной ряд должен иметь отметки времени");
         }
     }
+
+    public TimeSeries getModel() throws ModelingException {
+        if (model == null) {
+            makeModel();
+        }
+        return model;
+    }
 }

src/main/java/ru/ulstu/tsMethods/exponential/AddTrendNoSeason.java

@@ -0,0 +1,61 @@
+package ru.ulstu.tsMethods.exponential;
+
+import ru.ulstu.models.TimeSeries;
+import ru.ulstu.models.exceptions.ModelingException;
+import ru.ulstu.tsMethods.TimeSeriesMethod;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import static ru.ulstu.tsMethods.exponential.ExponentialParamName.ALPHA;
+import static ru.ulstu.tsMethods.exponential.ExponentialParamName.BETA;
+
+public class AddTrendNoSeason extends TimeSeriesMethod {
+    private final ExponentialMethodParams exponentialMethodParams;
+    private final List<Double> sComponent = new ArrayList<>();
+    private final List<Double> tComponent = new ArrayList<>();
+
+    public AddTrendNoSeason(TimeSeries timeSeries, ExponentialMethodParams exponentialMethodParams) throws ModelingException {
+        super(timeSeries);
+        this.exponentialMethodParams = exponentialMethodParams;
+    }
+
+    @Override
+    protected TimeSeries getModelOfValidTimeSeries() throws ModelingException {
+        sComponent.clear();
+        tComponent.clear();
+        sComponent.add(originalTimeSeries.getFirstValue().getValue());
+        tComponent.add(originalTimeSeries.getValues().get(1).getValue() - originalTimeSeries.getValues().get(0).getValue());
+        TimeSeries model = new TimeSeries("Model of " + originalTimeSeries.getName());
+        model.addValue(originalTimeSeries.getFirstValue());
+        //выполняется проход модели по сглаживанию
+        for (int t = 1; t < originalTimeSeries.getValues().size(); t++) {
+            sComponent.add(exponentialMethodParams.getValue(ALPHA) * originalTimeSeries.getNumericValue(t)
+                    + (1 - exponentialMethodParams.getValue(ALPHA))
+                    * (sComponent.get(t - 1) - tComponent.get(t - 1)));
+
+            tComponent.add(exponentialMethodParams.getValue(BETA)
+                    * (sComponent.get(t) - sComponent.get(t - 1))
+                    + (1 - exponentialMethodParams.getValue(BETA)) * tComponent.get(t - 1));
+            model.addValue(originalTimeSeries.getValues().get(t), sComponent.get(sComponent.size() - 1));
+        }
+        return model;
+    }
+
+    @Override
+    protected TimeSeries makeForecast(TimeSeries forecast) throws ModelingException {
+        for (int t = 1; t < forecast.getLength(); t++) {
+            /*int indexOffsetForModel = t + getModel().getLength() - 2;
+            sComponent.add(exponentialMethodParams.getValue(ALPHA) * forecast.getNumericValue(t-1)
+                    + (1 - exponentialMethodParams.getValue(ALPHA))
+                    * (sComponent.get(indexOffsetForModel) - tComponent.get(indexOffsetForModel - 1)));
+
+            tComponent.add(exponentialMethodParams.getValue(BETA)
+                    * (sComponent.get(indexOffsetForModel) - sComponent.get(indexOffsetForModel - 1))
+                    + (1 - exponentialMethodParams.getValue(BETA)) * tComponent.get(indexOffsetForModel - 1));*/
+
+            forecast.getValues().get(t).setValue(sComponent.get(sComponent.size() - 1) + tComponent.get(tComponent.size() - 1) * t);
+        }
+        return forecast;
+    }
+}

src/main/java/ru/ulstu/tsMethods/exponential/ExponentialMethodParams.java

@@ -23,4 +23,8 @@ public class ExponentialMethodParams {
     public static ExponentialMethodParams of(ExponentialParamName param1, Double value1) {
         return new ExponentialMethodParams(ImmutableMap.of(param1, value1));
     }
+
+    public static ExponentialMethodParams of(ExponentialParamName param1, Double value1, ExponentialParamName param2, Double value2) {
+        return new ExponentialMethodParams(ImmutableMap.of(param1, value1, param2, value2));
+    }
 }

src/main/java/ru/ulstu/tsMethods/exponential/NoTrendNoSeason.java

@@ -1,43 +1,43 @@
 package ru.ulstu.tsMethods.exponential;
 
-import ru.ulstu.models.Forecast;
-import ru.ulstu.models.Model;
 import ru.ulstu.models.TimeSeries;
 import ru.ulstu.models.exceptions.ModelingException;
 import ru.ulstu.tsMethods.TimeSeriesMethod;
 
+import java.util.ArrayList;
+import java.util.List;
+
 import static ru.ulstu.tsMethods.exponential.ExponentialParamName.ALPHA;
 
 public class NoTrendNoSeason extends TimeSeriesMethod {
-    private ExponentialMethodParams exponentialMethodParams;
+    private final ExponentialMethodParams exponentialMethodParams;
+    private final List<Double> sComponent = new ArrayList<>();
 
-    public NoTrendNoSeason(ExponentialMethodParams exponentialMethodParams) {
+    public NoTrendNoSeason(TimeSeries timeSeries, ExponentialMethodParams exponentialMethodParams) throws ModelingException {
+        super(timeSeries);
         this.exponentialMethodParams = exponentialMethodParams;
     }
 
     @Override
-    protected Model getModelOfValidTimeSeries(TimeSeries timeSeries) throws ModelingException {
+    protected TimeSeries getModelOfValidTimeSeries() throws ModelingException {
-        Model model = new Model(timeSeries);
+        sComponent.clear();
-        model.addValue(timeSeries.getFirstValue());
+        sComponent.add(originalTimeSeries.getFirstValue().getValue());
+        TimeSeries model = new TimeSeries("Model of " + originalTimeSeries.getName());
+        model.addValue(originalTimeSeries.getFirstValue());
         //выполняется проход модели по сглаживанию
-        for (int t = 1; t < timeSeries.getValues().size(); t++) {
+        for (int t = 1; t < originalTimeSeries.getValues().size(); t++) {
-            model.addValue(timeSeries.getValues().get(t),
+            sComponent.add(sComponent.get(t - 1)
-                    (1 - exponentialMethodParams.getValue(ALPHA)) * timeSeries.getNumericValue(t)
+                    + exponentialMethodParams.getValue(ALPHA)
-                            + exponentialMethodParams.getValue(ALPHA) * model.getModelTimeSeries().getValues().get(t - 1).getValue());
+                    * (originalTimeSeries.getNumericValue(t) - sComponent.get(t - 1)));
+            model.addValue(originalTimeSeries.getValues().get(t), sComponent.get(sComponent.size() - 1));
         }
         return model;
     }
 
     @Override
-    protected Forecast makeForecast(Forecast forecast) {
+    protected TimeSeries makeForecast(TimeSeries forecast) {
-        forecast.getForecastTimeSeries()
+        for (int t = 1; t < forecast.getLength(); t++) {
-                .getFirstValue()
+            forecast.getValues().get(t).setValue(forecast.getValues().get(t - 1).getValue());
-                .setValue(forecast.getModel().getModelTimeSeries().getLastValue().getValue());
-        for (int t = 1; t < forecast.getForecastTimeSeries().getLength(); t++) {
-            forecast.getForecastTimeSeries()
-                    .getValues()
-                    .get(t)
-                    .setValue(forecast.getForecastTimeSeries().getValues().get(t - 1).getValue());
         }
         return forecast;
     }