- Timestamp:
- 02/03/15 14:00:39 (10 years ago)
- Location:
- stable
- Files:
-
- 24 edited
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- Added
- Removed
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stable
- Property svn:mergeinfo changed
/trunk/sources merged: 11313,11348,11434-11435,11441
- Property svn:mergeinfo changed
-
stable/HeuristicLab.Problems.Instances.DataAnalysis
- Property svn:mergeinfo changed
/trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis merged: 11313,11348,11434-11435
- Property svn:mergeinfo changed
-
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionEight.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 data.Add(ValueGenerator.GenerateSteps(0 , 100, 1).ToList());51 data[0].AddRange(ValueGenerator.GenerateSteps(0 , 100, 0.1));50 data.Add(ValueGenerator.GenerateSteps(0m, 100, 1).Select(v => (double)v).ToList()); 51 data[0].AddRange(ValueGenerator.GenerateSteps(0m, 100, 0.1m).Select(v => (double)v)); 52 52 53 53 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionEleven.cs
r11170 r11868 49 49 protected override List<List<double>> GenerateValues() { 50 50 List<List<double>> data = new List<List<double>>(); 51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01 ).ToList();51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01m).Select(v => (double)v).ToList(); 52 52 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 53 53 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionFifteen.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01 ).ToList();50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01m).Select(v => (double)v).ToList(); 51 51 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 52 52 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionFour.cs
r11170 r11868 49 49 protected override List<List<double>> GenerateValues() { 50 50 List<List<double>> data = new List<List<double>>(); 51 data.Add(ValueGenerator.GenerateSteps(0, 10, 0.05 ).ToList());52 data[0].AddRange(ValueGenerator.GenerateSteps(0.05 , 10.05, 0.05));51 data.Add(ValueGenerator.GenerateSteps(0, 10, 0.05m).Select(v => (double)v).ToList()); 52 data[0].AddRange(ValueGenerator.GenerateSteps(0.05m, 10.05m, 0.05m).Select(v => (double)v)); 53 53 54 54 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionFourteen.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01 ).ToList();50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01m).Select(v => (double) v).ToList(); 51 51 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 52 52 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionNine.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 data.Add(ValueGenerator.GenerateSteps(0 , 100, 1).ToList());51 data[0].AddRange(ValueGenerator.GenerateSteps(0, 100, 0.1 ));50 data.Add(ValueGenerator.GenerateSteps(0m, 100, 1).Select(v => (double)v).ToList()); 51 data[0].AddRange(ValueGenerator.GenerateSteps(0, 100, 0.1m).Select(v => (double)v)); 52 52 53 53 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionOne.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 data.Add(ValueGenerator.GenerateSteps(-1, 1, 0.1 ).ToList());51 data[0].AddRange(ValueGenerator.GenerateSteps(-1, 1, 0.001 ));50 data.Add(ValueGenerator.GenerateSteps(-1, 1, 0.1m).Select(v => (double)v).ToList()); 51 data[0].AddRange(ValueGenerator.GenerateSteps(-1, 1, 0.001m).Select(v => (double)v)); 52 52 53 53 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionSeven.cs
r11170 r11868 49 49 protected override List<List<double>> GenerateValues() { 50 50 List<List<double>> data = new List<List<double>>(); 51 data.Add(ValueGenerator.GenerateSteps(1 , 100, 1).ToList());52 data[0].AddRange(ValueGenerator.GenerateSteps(1 , 100, 0.1));51 data.Add(ValueGenerator.GenerateSteps(1m, 100, 1).Select(v => (double)v).ToList()); 52 data[0].AddRange(ValueGenerator.GenerateSteps(1m, 100, 0.1m).Select(v => (double)v)); 53 53 54 54 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionSix.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 data.Add(ValueGenerator.GenerateSteps(1 , 50, 1).ToList());51 data[0].AddRange(ValueGenerator.GenerateSteps(1 , 120, 1));50 data.Add(ValueGenerator.GenerateSteps(1m, 50, 1).Select(v => (double)v).ToList()); 51 data[0].AddRange(ValueGenerator.GenerateSteps(1m, 120, 1).Select(v => (double)v)); 52 52 53 53 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionTen.cs
r11170 r11868 49 49 List<List<double>> data = new List<List<double>>(); 50 50 51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(0, 1, 0.01 ).ToList();51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(0, 1, 0.01m).Select(v => (double)v).ToList(); 52 52 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 53 53 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionThirteen.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01 ).ToList();50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01m).Select(v => (double)v).ToList(); 51 51 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 52 52 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionThree.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 data.Add(ValueGenerator.GenerateSteps(-3, 3, 0.1 ).ToList());51 data[0].AddRange(ValueGenerator.GenerateSteps(-3, 3, 0.001 ));50 data.Add(ValueGenerator.GenerateSteps(-3, 3, 0.1m).Select(v => (double)v).ToList()); 51 data[0].AddRange(ValueGenerator.GenerateSteps(-3, 3, 0.001m).Select(v => (double)v)); 52 52 53 53 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionTwelve.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01 ).ToList();50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-3, 3, 0.01m).Select(v => (double)v).ToList(); 51 51 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 52 52 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Keijzer/KeijzerFunctionTwo.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 data.Add(ValueGenerator.GenerateSteps(-2, 2, 0.1 ).ToList());51 data[0].AddRange(ValueGenerator.GenerateSteps(-2, 2, 0.001 ));50 data.Add(ValueGenerator.GenerateSteps(-2, 2, 0.1m).Select(v => (double)v).ToList()); 51 data[0].AddRange(ValueGenerator.GenerateSteps(-2, 2, 0.001m).Select(v => (double)v)); 52 52 53 53 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/ValueGenerator.cs
r11170 r11868 31 31 32 32 /// <summary> 33 /// Generates a sequence of evenly spaced points between start and end (inclusive!). 33 /// Generates a sequence of evenly spaced points by returning the start value and adding the stepwidth until the end is reached or surpassed. 34 /// 34 35 /// </summary> 35 36 /// <param name="start">The smallest and first value of the sequence.</param> 36 37 /// <param name="end">The largest and last value of the sequence.</param> 37 38 /// <param name="stepWidth">The step size between subsequent values.</param> 38 /// <returns>An sequence of values from start to end (inclusive)</returns> 39 public static IEnumerable<double> GenerateSteps(double start, double end, double stepWidth) { 40 if (start > end) throw new ArgumentException("start must be less than or equal end."); 41 if (stepWidth <= 0) throw new ArgumentException("stepwith must be larger than zero.", "stepWidth"); 42 double x = start; 43 // x<=end could skip the last value because of numerical problems 44 while (x < end || x.IsAlmost(end)) { 39 /// <param name="includeEnd">Determines if the end should be included in the sequence regardless if the end is divisible by the stepwidth.</param> 40 /// <returns>A sequence of values from start to end (inclusive)</returns> 41 [Obsolete("It is recommended to use the decimal overload to achieve a higher numerical accuracy.")] 42 public static IEnumerable<double> GenerateSteps(double start, double end, double stepWidth, bool includeEnd = false) { 43 //mkommend: IEnumerable.Cast fails due to boxing and unboxing of the involved types 44 // http://referencesource.microsoft.com/#System.Core/System/Linq/Enumerable.cs#27bb217a6d5457ec 45 // http://blogs.msdn.com/b/ericlippert/archive/2009/03/19/representation-and-identity.aspx 46 47 return GenerateSteps((decimal)start, (decimal)end, (decimal)stepWidth, includeEnd).Select(x => (double)x); 48 } 49 50 /// <summary> 51 /// Generates a sequence of evenly spaced points by returning the start value and adding the stepwidth until the end is reached or surpassed. 52 /// </summary> 53 /// <param name="start">The smallest and first value of the sequence.</param> 54 /// <param name="end">The largest and last value of the sequence.</param> 55 /// <param name="stepWidth">The step size between subsequent values.</param> 56 /// /// <param name="includeEnd">Determines if the end should be included in the sequence regardless if the end is divisible by the stepwidth.</param> 57 /// <returns>A sequence of values from start to end</returns> 58 public static IEnumerable<decimal> GenerateSteps(decimal start, decimal end, decimal stepWidth, bool includeEnd = false) { 59 if (stepWidth == 0) 60 throw new ArgumentException("The step width cannot be zero."); 61 if (start < end && stepWidth < 0) 62 throw new ArgumentException("The step width must be larger than zero for increasing sequences (start < end)."); 63 if (start > end && stepWidth > 0) 64 throw new ArgumentException("The step width must be smaller than zero for decreasing sequences (start > end)."); 65 66 decimal x = start; 67 while (x <= end) { 45 68 yield return x; 46 69 x += stepWidth; 47 70 } 71 if (x - stepWidth < end && includeEnd) yield return end; 48 72 } 49 73 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Various/SpatialCoevolution.cs
r11170 r11868 53 53 List<List<double>> data = new List<List<double>>(); 54 54 55 List<double> evenlySpacedSequence = ValueGenerator.GenerateSteps(-5, 5, 0.4 ).ToList();55 List<double> evenlySpacedSequence = ValueGenerator.GenerateSteps(-5, 5, 0.4m).Select(v => (double)v).ToList(); 56 56 List<List<double>> trainingData = new List<List<double>>() { evenlySpacedSequence, evenlySpacedSequence }; 57 57 var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(trainingData).ToList(); -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/KotanchekFunction.cs
r11170 r11868 49 49 List<List<double>> data = new List<List<double>>(); 50 50 51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.2 , 4.2, 0.1).ToList();51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.2m, 4.2m, 0.1m).Select(v => (double)v).ToList(); 52 52 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 53 53 var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>(); -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/RationalPolynomialThreeDimensional.cs
r11170 r11868 55 55 56 56 List<List<double>> testData = new List<List<double>>() { 57 ValueGenerator.GenerateSteps(-0.05 , 2.05, 0.15).ToList(),58 ValueGenerator.GenerateSteps( 0.95 , 2.05, 0.1).ToList(),59 ValueGenerator.GenerateSteps(-0.05 , 2.05, 0.15).ToList()57 ValueGenerator.GenerateSteps(-0.05m, 2.05m, 0.15m).Select(v => (double)v).ToList(), 58 ValueGenerator.GenerateSteps( 0.95m, 2.05m, 0.1m).Select(v => (double)v).ToList(), 59 ValueGenerator.GenerateSteps(-0.05m, 2.05m, 0.15m).Select(v => (double)v).ToList() 60 60 }; 61 61 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/RationalPolynomialTwoDimensional.cs
r11170 r11868 49 49 List<List<double>> data = new List<List<double>>(); 50 50 51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.25 , 6.35, 0.2).ToList();51 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.25m, 6.35m, 0.2m).Select(v => (double)v).ToList(); 52 52 53 53 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/SalutowiczFunctionOneDimensional.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 data.Add(ValueGenerator.GenerateSteps(0.05 , 10, 0.1).ToList());51 data[0].AddRange(ValueGenerator.GenerateSteps(-0.5 , 10.5, 0.05));50 data.Add(ValueGenerator.GenerateSteps(0.05m, 10, 0.1m).Select(v => (double)v).ToList()); 51 data[0].AddRange(ValueGenerator.GenerateSteps(-0.5m, 10.5m, 0.05m).Select(v => (double)v)); 52 52 53 53 double x; -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/SalutowiczFunctionTwoDimensional.cs
r11170 r11868 49 49 List<List<double>> data = new List<List<double>>(); 50 50 List<List<double>> trainingData = new List<List<double>>() { 51 ValueGenerator.GenerateSteps(0.05 , 10, 0.1).ToList(),52 ValueGenerator.GenerateSteps(0.05 , 10.05, 2).ToList()51 ValueGenerator.GenerateSteps(0.05m, 10, 0.1m).Select(v => (double)v).ToList(), 52 ValueGenerator.GenerateSteps(0.05m, 10.05m, 2).Select(v => (double)v).ToList() 53 53 }; 54 54 55 55 List<List<double>> testData = new List<List<double>>() { 56 ValueGenerator.GenerateSteps(-0.5 , 10.5, 0.05).ToList(),57 ValueGenerator.GenerateSteps(-0.5 , 10.5, 0.5).ToList()56 ValueGenerator.GenerateSteps(-0.5m, 10.5m, 0.05m).Select(v => (double)v).ToList(), 57 ValueGenerator.GenerateSteps(-0.5m, 10.5m, 0.5m).Select(v => (double)v).ToList() 58 58 }; 59 59 -
stable/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Vladislavleva/SineCosineFunction.cs
r11170 r11868 48 48 protected override List<List<double>> GenerateValues() { 49 49 List<List<double>> data = new List<List<double>>(); 50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.05 , 6.05, 0.02).ToList();50 List<double> oneVariableTestData = ValueGenerator.GenerateSteps(-0.05m, 6.05m, 0.02m).Select(v => (double)v).ToList(); 51 51 List<List<double>> testData = new List<List<double>>() { oneVariableTestData, oneVariableTestData }; 52 52 var combinations = ValueGenerator.GenerateAllCombinationsOfValuesInLists(testData).ToList<IEnumerable<double>>();
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