using System.Collections.Generic; using System.Linq; using HeuristicLab.Common; using HeuristicLab.Core; using HeuristicLab.Data; using HeuristicLab.Parameters; using HEAL.Attic; namespace HeuristicLab.Problems.DataAnalysis { [StorableType("F0DC4951-64DF-4058-8E87-748D0FA1AA21")] [Item("Shift Standard Distribution Transformation", "f(x) = ((x - m_org) / s_org ) * s_tar + m_tar | Represents Transformation to unit standard deviation and additional linear transformation to a target Mean and Standard deviation")] public class ShiftStandardDistributionTransformation : Transformation { protected const string OriginalMeanParameterName = "Original Mean"; protected const string OriginalStandardDeviationParameterName = "Original Standard Deviation"; protected const string MeanParameterName = "Mean"; protected const string StandardDeviationParameterName = "Standard Deviation"; #region Parameters public IValueParameter OriginalMeanParameter { get { return (IValueParameter)Parameters[OriginalMeanParameterName]; } } public IValueParameter OriginalStandardDeviationParameter { get { return (IValueParameter)Parameters[OriginalStandardDeviationParameterName]; } } public IValueParameter MeanParameter { get { return (IValueParameter)Parameters[MeanParameterName]; } } public IValueParameter StandardDeviationParameter { get { return (IValueParameter)Parameters[StandardDeviationParameterName]; } } #endregion #region properties public override string ShortName { get { return "Std"; } } public double OriginalMean { get { return OriginalMeanParameter.Value.Value; } set { OriginalMeanParameter.Value.Value = value; } } public double OriginalStandardDeviation { get { return OriginalStandardDeviationParameter.Value.Value; } set { OriginalStandardDeviationParameter.Value.Value = value; } } public double Mean { get { return MeanParameter.Value.Value; } } public double StandardDeviation { get { return StandardDeviationParameter.Value.Value; } } #endregion [StorableConstructor] protected ShiftStandardDistributionTransformation(StorableConstructorFlag _) : base(_) { } protected ShiftStandardDistributionTransformation(ShiftStandardDistributionTransformation original, Cloner cloner) : base(original, cloner) { } public ShiftStandardDistributionTransformation(IEnumerable allowedColumns) : base(allowedColumns) { Parameters.Add(new ValueParameter(OriginalMeanParameterName, "m_org | Mean value of the original data's deviation.", new DoubleValue())); Parameters.Add(new ValueParameter(OriginalStandardDeviationParameterName, "s_org | Standard deviation of the original data.", new DoubleValue())); OriginalMeanParameter.Hidden = true; OriginalStandardDeviationParameter.Hidden = true; Parameters.Add(new ValueParameter(MeanParameterName, "m_tar | Mean value for the target deviation.", new DoubleValue(0.0))); Parameters.Add(new ValueParameter(StandardDeviationParameterName, "s_tar | Standard deviation for the target data.", new DoubleValue(1.0))); } public override IDeepCloneable Clone(Cloner cloner) { return new ShiftStandardDistributionTransformation(this, cloner); } public override IEnumerable Apply(IEnumerable data) { if (OriginalStandardDeviation.IsAlmost(0.0)) { return data; } var old_m = OriginalMean; var old_s = OriginalStandardDeviation; var m = Mean; var s = StandardDeviation; return data .Select(d => (d - old_m) / old_s) // standardized .Select(d => d * s + m); } public override bool Check(IEnumerable data, out string errorMsg) { ConfigureParameters(data); errorMsg = ""; if (OriginalStandardDeviation.IsAlmost(0.0)) { errorMsg = "Standard deviaton for the original data is 0.0, Transformation cannot be applied onto these values."; return false; } return true; } public override void ConfigureParameters(IEnumerable data) { OriginalStandardDeviation = data.StandardDeviation(); OriginalMean = data.Average(); } } }