refactor polynomial model class and deseasonality functions, refine comments

Author: [email protected]

src/Microsoft.ML.TimeSeries/Deseasonality/DeseasonalityBase.cs

@@ -10,8 +10,4 @@
     <ProjectReference Include="..\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
     <ProjectReference Include="..\Microsoft.ML.Transforms\Microsoft.ML.Transforms.csproj" />
   </ItemGroup>
-
-  <ItemGroup>
-    <Folder Include="Deseasonality\" />
-  </ItemGroup>
 </Project>

src/Microsoft.ML.TimeSeries/Deseasonality/MeanDeseasonality.cs

@@ -0,0 +1,119 @@
+using System;
+using System.Collections.Generic;
+
+namespace Microsoft.ML.TimeSeries
+{
+    internal interface IDeseasonality
+    {
+        public abstract void Deseasonality(ref double[] values, int period, ref double[] results);
+    }
+
+    internal sealed class MeanDeseasonality : IDeseasonality
+    {
+        private double[] _circularComponent;
+
+        public void Deseasonality(ref double[] values, int period, ref double[] results)
+        {
+            Array.Resize(ref _circularComponent, period);
+
+            var length = values.Length;
+
+            // Initialize the circular component to 0.
+            for (int i = 0; i < period; ++i)
+            {
+                _circularComponent[i] = 0;
+            }
+
+            // Sum up values that locates at the same position in one period.
+            for (int i = 0; i < length; ++i)
+            {
+                var indexInPeriod = i % period;
+                _circularComponent[indexInPeriod] += values[i];
+            }
+
+            // Calculate the mean value as circular component.
+            var cnt = (length - 1) / period;
+            var rest = (length - 1) % period;
+            for (int i = 0; i < period; ++i)
+            {
+                var lastCircle = i <= rest ? 1 : 0;
+                _circularComponent[i] = _circularComponent[i] / (cnt + lastCircle);
+            }
+
+            // Substract the circular component from the original series.
+            for (int i = 0; i < length; ++i)
+            {
+                var indexInPeriod = i % period;
+                results[i] -= _circularComponent[indexInPeriod];
+            }
+        }
+    }
+
+    internal sealed class MedianDeseasonality : IDeseasonality
+    {
+        private List<double>[] _subSeries;
+        private double[] _circularComponent;
+
+        public void Deseasonality(ref double[] values, int period, ref double[] results)
+        {
+            Array.Resize(ref _circularComponent, period);
+            Array.Resize(ref _subSeries, period);
+
+            var length = values.Length;
+
+            for (int i = 0; i < period; ++i)
+            {
+                _subSeries[i] = new List<double>();
+            }
+
+            // Split the original series into #period subseries.
+            for (int i = 0; i < length; ++i)
+            {
+                var indexInPeriod = i % period;
+                _subSeries[indexInPeriod].Add(values[i]);
+            }
+
+            // Calculate the median value as circular component.
+            for (int i = 0; i < period; ++i)
+            {
+                _circularComponent[i] = MathUtility.QuickMedian(_subSeries[i]);
+            }
+
+            // Substract the circular component from the original series.
+            for (int i = 0; i < length; ++i)
+            {
+                var indexInPeriod = i % period;
+                results[i] -= _circularComponent[indexInPeriod];
+            }
+        }
+    }
+
+    internal sealed class StlDeseasonality : IDeseasonality
+    {
+        private readonly InnerStl _stl;
+
+        public StlDeseasonality()
+        {
+            _stl = new InnerStl(true);
+        }
+
+        public void Deseasonality(ref double[] values, int period, ref double[] results)
+        {
+            bool success = _stl.Decomposition(values, period);
+            if (success)
+            {
+                for (int i = 0; i < _stl.Residual.Count; ++i)
+                {
+                    results[i] = _stl.Residual[i];
+                }
+            }
+            else
+            {
+                for (int i = 0; i < values.Length; ++i)
+                {
+                    results[i] = values[i];
+                }
+            }
+        }
+    }
+}