add first method

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

@@ -3,10 +3,7 @@ package ru.ulstu.controllers;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.http.HttpStatus;
 import org.springframework.http.ResponseEntity;
-import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.*;
-import org.springframework.web.bind.annotation.RequestMethod;
-import org.springframework.web.bind.annotation.RequestParam;
-import org.springframework.web.bind.annotation.RestController;
 import ru.ulstu.configurations.ApiConfiguration;
 import ru.ulstu.models.TimeSeries;
 import ru.ulstu.services.TimeSeriesService;
@@ -31,4 +28,9 @@ public class TimeSeriesController {
     public ResponseEntity<TimeSeries> getRandomTimeSeries(@RequestParam("length") int length) {
         return new ResponseEntity<>(timeSeriesService.getRandomTimeSeries(length), HttpStatus.OK);
     }
+
+    @RequestMapping(value = "ts.get_forecast", method = RequestMethod.POST)
+    public ResponseEntity<TimeSeries> getForecastTimeSeries(@RequestBody TimeSeries timeSeries) {
+        return new ResponseEntity<>(timeSeriesService.getForecast(timeSeries), HttpStatus.OK);
+    }
 }

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

@@ -1,5 +1,8 @@
 package ru.ulstu.models;
 
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
 import java.util.ArrayList;
 import java.util.List;
 
@@ -11,6 +14,16 @@ public class TimeSeries {
         this.name = name;
     }
 
+    @JsonCreator
+    public TimeSeries(@JsonProperty(value = "values") List<TimeSeriesValue> values, @JsonProperty(value = "name") String name) {
+        this.values = values;
+        this.name = name;
+    }
+
+    public TimeSeries() {
+
+    }
+
     public List<TimeSeriesValue> getValues() {
         return values;
     }
@@ -26,4 +39,20 @@ public class TimeSeries {
     public void setName(String name) {
         this.name = name;
     }
+
+    public boolean isEmpty() {
+        return values.isEmpty();
+    }
+
+    public void addValue(TimeSeriesValue timeSeriesValue) {
+        values.add(timeSeriesValue);
+    }
+
+    public void addValue(TimeSeriesValue basedOnValue, Double value) {
+        values.add(new TimeSeriesValue(basedOnValue.getDate().plusDays(1), value));
+    }
+
+    public TimeSeriesValue getLastValue() {
+        return values.get(values.size()-1);
+    }
 }

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

@@ -1,12 +1,16 @@
 package ru.ulstu.models;
 
+import com.fasterxml.jackson.annotation.JsonCreator;
+import com.fasterxml.jackson.annotation.JsonProperty;
+
 import java.time.LocalDate;
 
 public class TimeSeriesValue {
     private LocalDate date;
     private Double value;
 
-    public TimeSeriesValue(LocalDate date, Double value) {
+    @JsonCreator
+    public TimeSeriesValue(@JsonProperty(value="date") LocalDate date, @JsonProperty(value = "value") Double value) {
         this.date = date;
         this.value = value;
     }

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

@@ -3,6 +3,7 @@ package ru.ulstu.services;
 import org.springframework.stereotype.Service;
 import ru.ulstu.models.TimeSeries;
 import ru.ulstu.models.TimeSeriesValue;
+import ru.ulstu.tsMethods.exponential.NoTrendNoSeason;
 
 import java.time.LocalDate;
 
@@ -18,4 +19,11 @@ public class TimeSeriesService {
         }
         return ts;
     }
+
+    public TimeSeries getForecast(TimeSeries timeSeries) {
+        NoTrendNoSeason nn = new NoTrendNoSeason(timeSeries, 5);
+        nn.setAlpa(0.1);
+        nn.createModel();
+        return nn.getForecastTimeSeries();
+    }
 }

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

@@ -0,0 +1,5 @@
+package ru.ulstu.tsMethods;
+
+public enum Param {
+    ALPHA
+}

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

@@ -0,0 +1,37 @@
+package ru.ulstu.tsMethods;
+
+import ru.ulstu.models.TimeSeries;
+
+import java.util.HashMap;
+import java.util.Map;
+
+public abstract class TimeSeriesMethod {
+    protected TimeSeries originalTimeSeries;
+    protected TimeSeries modelTimeSeries;
+    protected TimeSeries forecastTimeSeries;
+    protected int countForecast;
+    protected Map<Param, Double> parameters = new HashMap<>();
+
+    protected void init() {
+        modelTimeSeries = new TimeSeries("Model time series of '" + originalTimeSeries.getName() + "'");
+        forecastTimeSeries = new TimeSeries("Forecast time series of '" + originalTimeSeries.getName() + "'");
+    }
+
+    public TimeSeries getOriginalTimeSeries() {
+        return originalTimeSeries;
+    }
+
+    public TimeSeries getModelTimeSeries() {
+        return modelTimeSeries;
+    }
+
+    public int getCountForecast() {
+        return countForecast;
+    }
+
+    public TimeSeries getForecastTimeSeries() {
+        return forecastTimeSeries;
+    }
+
+    public abstract void createModel();
+}

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

@@ -0,0 +1,45 @@
+package ru.ulstu.tsMethods.exponential;
+
+import ru.ulstu.models.TimeSeries;
+import ru.ulstu.tsMethods.Param;
+import ru.ulstu.tsMethods.TimeSeriesMethod;
+
+public class NoTrendNoSeason extends TimeSeriesMethod {
+    public NoTrendNoSeason(TimeSeries originalTimeSeries, int countForecast) {
+        this.originalTimeSeries = originalTimeSeries;
+        this.countForecast = countForecast;
+        if (originalTimeSeries.isEmpty()) {
+            throw new RuntimeException("Time series must not empty");
+        }
+    }
+
+    @Override
+    protected void init() {
+        super.init();
+        modelTimeSeries.addValue(originalTimeSeries.getValues().get(0));
+        forecastTimeSeries.addValue(originalTimeSeries.getValues().get(0));
+        parameters.put(Param.ALPHA, 1.0);
+    }
+
+    public void setAlpa(double value) {
+        parameters.put(Param.ALPHA, value);
+    }
+
+    @Override
+    public void createModel() {
+        init();
+        double e;
+
+        //выполняется проход модели по сглаживанию и прогнозированию countPointForecast точек
+        for (int t = 0; t < originalTimeSeries.getValues().size() - 1 + countForecast; t++) {
+            // пока не дошли до конца ряда - сглаживаем, иначе строим прогноз
+            if (t < originalTimeSeries.getValues().size()) {
+                e = originalTimeSeries.getValues().get(t).getValue() - forecastTimeSeries.getValues().get(t).getValue();
+            } else {
+                e = 0;
+            }
+            modelTimeSeries.addValue(modelTimeSeries.getLastValue(), modelTimeSeries.getValues().get(t).getValue() + parameters.get(Param.ALPHA) * e);    //  уровень
+            forecastTimeSeries.addValue(modelTimeSeries.getLastValue());        //  прогноз
+        }
+    }
+}