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FunctionRegression domain: ported performance improvements from SharpNeat 4.x branch.
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9 files changed

+56
-38
lines changed

9 files changed

+56
-38
lines changed

‎src/SharpNeatDomains/FunctionRegression/FnRegressionEvaluator.cs

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -9,7 +9,7 @@
99
* You should have received a copy of the MIT License
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* along with SharpNEAT; if not, see https://opensource.org/licenses/MIT.
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*/
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using System;
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using Redzen;
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using SharpNeat.Core;
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using SharpNeat.Phenomes;
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@@ -103,11 +103,11 @@ public FitnessInfo Evaluate(IBlackBox box)
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FnRegressionUtils.CalcGradients(_paramSamplingInfo, yArr, gradientArr);
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105105
// Calc y position mean squared error (MSE), and apply weighting.
106-
double yMse = FnRegressionUtils.CalcMeanSquaredError(yArr, _yArrTarget);
106+
double yMse = MathArrayUtils.MeanSquaredDelta(yArr, _yArrTarget);
107107
yMse *= _yMseWeight;
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109109
// Calc gradient mean squared error.
110-
double gradientMse = FnRegressionUtils.CalcMeanSquaredError(gradientArr, _gradientArrTarget);
110+
double gradientMse = MathArrayUtils.MeanSquaredDelta(gradientArr, _gradientArrTarget);
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gradientMse *= _gradientMseWeight;
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// Calc fitness as the inverse of MSE (higher value is fitter).

‎src/SharpNeatDomains/FunctionRegression/FnRegressionUtils.cs

Lines changed: 43 additions & 25 deletions
Original file line numberDiff line numberDiff line change
@@ -10,7 +10,7 @@
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* along with SharpNEAT; if not, see https://opensource.org/licenses/MIT.
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*/
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using System;
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using System.Diagnostics;
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using System.Numerics;
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namespace SharpNeat.Domains.FunctionRegression
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{
@@ -37,37 +37,59 @@ public static void CalcFunctionMidAndScale(IFunction fn, ParamSamplingInfo param
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mid = ((min+max) / 2.0);
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}
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40-
public static void CalcGradients (ParamSamplingInfo paramSamplingInfo, double[] yArr, double[] gradientArr)
40+
public static void CalcGradients(
41+
ParamSamplingInfo paramSamplingInfo,
42+
double[] yArr,
43+
double[] gradientArr)
4144
{
45+
// Notes.
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// The gradient at a sample point is approximated by taking the gradient of the line between the two
47+
// sample points either side of that point. For the first and last sample points we take the gradient
48+
// of the line between the sample point and its single adjacent sample point (as an alternative we could
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// sample an additional point at each end that doesn't get used for the function regression evaluation.
50+
//
51+
// This approach is rather crude, but fast. A better approach might be to do a polynomial regression on
52+
// the sample point and its nearest two adjacent samples, and then take the gradient of the polynomial
53+
// regression at the required point; obviously that would required more computational work to do so may
54+
// not be beneficial in the overall context of an evolutionary algorithm.
55+
//
56+
// Furthermore, the difference between this gradient approximation and the true gradient decreases with
57+
// increases sample density, therefore this is a reasonable approach *if* the sample density is
58+
// sufficiently high.
59+
4260
// Handle the end points as special cases.
4361
// First point.
4462
double[] xArr = paramSamplingInfo._xArr;
4563
gradientArr[0] = CalcGradient(xArr[0], yArr[0], xArr[1], yArr[1]);
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4765
// Intermediate points.
48-
for(int i=1; i< xArr.Length-1; i++) {
49-
gradientArr[i] = CalcGradient(xArr[i-1], yArr[i-1], xArr[i+1], yArr[i+1]);
50-
}
66+
int width = Vector<double>.Count;
67+
int i=1;
68+
for(; i < xArr.Length - width - 1; i += width)
69+
{
70+
// Calc a block of x deltas.
71+
var vecLeft = new Vector<double>(xArr, i - 1);
72+
var vecRight = new Vector<double>(xArr, i + 1);
73+
var xVecDelta = vecRight - vecLeft;
5174

52-
// Last point.
53-
int lastIdx = xArr.Length-1;
54-
gradientArr[lastIdx] = CalcGradient(xArr[lastIdx-1], yArr[lastIdx-1], xArr[lastIdx], yArr[lastIdx]);
55-
}
75+
// Calc a block of y deltas.
76+
vecLeft = new Vector<double>(yArr, i - 1);
77+
vecRight = new Vector<double>(yArr, i + 1);
78+
var yVecDelta = vecRight - vecLeft;
5679

57-
public static double CalcMeanSquaredError(double[] a, double[] b)
58-
{
59-
Debug.Assert(a.Length == b.Length);
80+
// Divide the y's by x's to obtain the gradients.
81+
var gradientVec = yVecDelta / xVecDelta;
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61-
// Calc sum(squared error).
62-
double total = 0.0;
63-
for(int i=0; i<a.Length; i++)
64-
{
65-
double err = a[i] - b[i];
66-
total += err * err;
83+
gradientVec.CopyTo(gradientArr, i);
84+
}
85+
86+
// Calc gradients for remaining intermediate points (if any).
87+
for (; i < xArr.Length - 1; i++) {
88+
gradientArr[i] = CalcGradient(xArr[i - 1], yArr[i - 1], xArr[i + 1], yArr[i + 1]);
6789
}
6890

69-
// Calculate mean squared error (MSE).
70-
return total / a.Length;
91+
// Last point.
92+
gradientArr[i] = CalcGradient(xArr[i - 1], yArr[i - 1], xArr[i], yArr[i]);
7193
}
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7395
#endregion
@@ -76,11 +98,7 @@ public static double CalcMeanSquaredError(double[] a, double[] b)
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7799
private static double CalcGradient(double x1, double y1, double x2, double y2)
78100
{
79-
double ydiff = y2 - y1;
80-
if(ydiff == 0.0) {
81-
return 0.0;
82-
}
83-
return ydiff / (x2-x1);
101+
return (y2 - y1) / (x2 - x1);
84102
}
85103

86104
#endregion

‎src/SharpNeatDomains/SharpNeatDomains.csproj

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<HintPath>..\packages\log4net.2.0.8\lib\net45-full\log4net.dll</HintPath>
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<Private>True</Private>
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</Reference>
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<Reference Include="Redzen, Version=8.0.0.0, Culture=neutral, PublicKeyToken=182843a4be0a74f7, processorArchitecture=MSIL">
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<HintPath>..\packages\Redzen.8.0.0\lib\netstandard2.0\Redzen.dll</HintPath>
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<Reference Include="Redzen, Version=9.0.0.0, Culture=neutral, PublicKeyToken=182843a4be0a74f7, processorArchitecture=MSIL">
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<HintPath>..\packages\Redzen.9.0.0-alpha1\lib\netstandard2.0\Redzen.dll</HintPath>
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</Reference>
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<Reference Include="System" />
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<Reference Include="System.Buffers, Version=4.0.3.0, Culture=neutral, PublicKeyToken=cc7b13ffcd2ddd51, processorArchitecture=MSIL">

‎src/SharpNeatDomains/packages.config

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<?xml version="1.0" encoding="utf-8"?>
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<packages>
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<package id="log4net" version="2.0.8" targetFramework="net461" />
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<package id="Redzen" version="8.0.0" targetFramework="net472" />
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<package id="Redzen" version="9.0.0-alpha1" targetFramework="net48" />
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<package id="System.Buffers" version="4.5.0" targetFramework="net471" />
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<package id="System.Memory" version="4.5.2" targetFramework="net471" />
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<package id="System.Numerics.Vectors" version="4.5.0" targetFramework="net471" />

‎src/SharpNeatDomainsExtra/SharpNeatDomainsExtra.csproj

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<HintPath>..\packages\log4net.2.0.8\lib\net45-full\log4net.dll</HintPath>
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<Private>True</Private>
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</Reference>
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<Reference Include="Redzen, Version=8.0.0.0, Culture=neutral, PublicKeyToken=182843a4be0a74f7, processorArchitecture=MSIL">
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<HintPath>..\packages\Redzen.8.0.0\lib\netstandard2.0\Redzen.dll</HintPath>
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<Reference Include="Redzen, Version=9.0.0.0, Culture=neutral, PublicKeyToken=182843a4be0a74f7, processorArchitecture=MSIL">
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<HintPath>..\packages\Redzen.9.0.0-alpha1\lib\netstandard2.0\Redzen.dll</HintPath>
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</Reference>
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<Reference Include="System" />
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<Reference Include="System.Buffers, Version=4.0.3.0, Culture=neutral, PublicKeyToken=cc7b13ffcd2ddd51, processorArchitecture=MSIL">

‎src/SharpNeatDomainsExtra/packages.config

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<packages>
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<package id="Box2DX" version="2.0.2.0" targetFramework="net461" />
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<package id="log4net" version="2.0.8" targetFramework="net461" />
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<package id="Redzen" version="8.0.0" targetFramework="net472" />
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<package id="Redzen" version="9.0.0-alpha1" targetFramework="net48" />
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<package id="System.Buffers" version="4.5.0" targetFramework="net471" />
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<package id="System.Memory" version="4.5.2" targetFramework="net471" />
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<package id="System.Numerics.Vectors" version="4.5.0" targetFramework="net471" />

‎src/SharpNeatGUI/SharpNeatGUI.csproj

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<HintPath>..\packages\log4net.2.0.8\lib\net45-full\log4net.dll</HintPath>
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<Private>True</Private>
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</Reference>
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<Reference Include="Redzen, Version=8.0.0.0, Culture=neutral, PublicKeyToken=182843a4be0a74f7, processorArchitecture=MSIL">
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<HintPath>..\packages\Redzen.8.0.0\lib\netstandard2.0\Redzen.dll</HintPath>
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<Reference Include="Redzen, Version=9.0.0.0, Culture=neutral, PublicKeyToken=182843a4be0a74f7, processorArchitecture=MSIL">
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<HintPath>..\packages\Redzen.9.0.0-alpha1\lib\netstandard2.0\Redzen.dll</HintPath>
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</Reference>
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<Reference Include="System" />
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<Reference Include="System.Buffers, Version=4.0.3.0, Culture=neutral, PublicKeyToken=cc7b13ffcd2ddd51, processorArchitecture=MSIL">

‎src/SharpNeatGUI/packages.config

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<?xml version="1.0" encoding="utf-8"?>
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<packages>
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<package id="log4net" version="2.0.8" targetFramework="net461" />
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<package id="Redzen" version="8.0.0" targetFramework="net472" />
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<package id="Redzen" version="9.0.0-alpha1" targetFramework="net48" />
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<package id="System.Buffers" version="4.5.0" targetFramework="net471" />
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<package id="System.Memory" version="4.5.2" targetFramework="net471" />
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<package id="System.Numerics.Vectors" version="4.5.0" targetFramework="net471" />

‎src/SharpNeatLib/SharpNeatLib.csproj

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<ItemGroup>
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<PackageReference Include="log4net" Version="2.0.8" />
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<PackageReference Include="Redzen" Version="8.0.0" />
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<PackageReference Include="Redzen" Version="9.0.0-alpha1" />
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</ItemGroup>
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<ItemGroup>

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