From b866e2509b24fbc227e47ed8d529f50da4d47e4e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Steinar=20Elgs=C3=A6ter?= <stelg@equinor.com>
Date: Thu, 1 Feb 2024 14:16:00 +0100
Subject: [PATCH] -added test and gain sched identify method to attempt to
estiamate a large number of gains when thresholds are given.
---
Dynamic/Identification/GainSchedIdentifier.cs | 46 ++++++++++++++-
.../Tests/GainSchedIdentifyTests.cs | 58 ++++++++++++++++---
2 files changed, 94 insertions(+), 10 deletions(-)
diff --git a/Dynamic/Identification/GainSchedIdentifier.cs b/Dynamic/Identification/GainSchedIdentifier.cs
index c44f1134..0bc01283 100644
--- a/Dynamic/Identification/GainSchedIdentifier.cs
+++ b/Dynamic/Identification/GainSchedIdentifier.cs
@@ -112,7 +112,48 @@ static public GainSchedParameters Identify(UnitDataSet dataSet, GainSchedFitting
/// <returns></returns>
public static GainSchedParameters IdentifyGainsForGivenThresholds(UnitDataSet dataSet, GainSchedFittingSpecs gsFittingSpecs)
{
- return null;
+ var vec = new Vec();
+ GainSchedParameters ret = new GainSchedParameters();
+ ret.GainSchedParameterIndex = gsFittingSpecs.uGainScheduledInputIndex;
+ ret.LinearGainThresholds = gsFittingSpecs.uGainThresholds;
+
+ const int WIDTH = 1; //
+
+ int number_of_inputs = dataSet.U.GetLength(1);
+ double gsVarMinU = vec.Min(Array2D<double>.GetColumn(dataSet.U, ret.GainSchedParameterIndex));
+ double gsVarMaxU = 0;
+ var linearGains = new List<double[]>();
+ for (int curGainIdx = 0; curGainIdx < ret.LinearGainThresholds.Count()+1; curGainIdx++)
+ {
+ double[] uMinFit = new double[number_of_inputs];
+ double[] uMaxFit = new double[number_of_inputs];
+
+ if (curGainIdx < ret.LinearGainThresholds.Count()- WIDTH)
+ gsVarMaxU = ret.LinearGainThresholds[curGainIdx+ WIDTH];//NB! +1
+ else
+ gsVarMaxU = vec.Max(Array2D<double>.GetColumn(dataSet.U, ret.GainSchedParameterIndex));
+ for (int idx = 0; idx < number_of_inputs; idx++)
+ {
+ if (idx == ret.GainSchedParameterIndex)
+ {
+ uMinFit[idx] = gsVarMinU;
+ uMaxFit[idx] = gsVarMaxU;
+ }
+ else
+ {
+ uMinFit[idx] = double.NaN;
+ uMaxFit[idx] = double.NaN;
+ }
+ }
+ var idResults = IdentifySingleGainForGivenThresholds(ref dataSet, uMinFit, uMaxFit);
+ if (curGainIdx>-1+ WIDTH)
+ gsVarMinU = ret.LinearGainThresholds[curGainIdx- WIDTH];
+ // if (idResults.Item1 != null)
+ linearGains.Add(idResults.Item1);
+ }
+ // final gain:above the highest threshold
+ ret.LinearGains = linearGains;
+ return ret;
}
@@ -203,7 +244,8 @@ private static (double[], double) IdentifySingleGainForGivenThresholds(ref UnitD
fittingSpecs.U_min_fit = u_min_fit;
fittingSpecs.U_max_fit = u_max_fit;
fittingSpecs.u0 = new double[] { u_min_fit[0] + (u_max_fit[0] - u_min_fit[0]) / 2 };
- var unitModel = UnitIdentifier.IdentifyLinear(ref dataSet, fittingSpecs, false); ;
+ // var unitModel = UnitIdentifier.IdentifyLinear(ref dataSet, fittingSpecs, false); ;
+ var unitModel = UnitIdentifier.IdentifyLinearAndStatic(ref dataSet, fittingSpecs, false); ;
var unitParams = unitModel.GetModelParameters();
return (unitParams.LinearGains, unitParams.TimeConstant_s);
diff --git a/TimeSeriesAnalysis.Tests/Tests/GainSchedIdentifyTests.cs b/TimeSeriesAnalysis.Tests/Tests/GainSchedIdentifyTests.cs
index fc75d3ee..086ac17e 100644
--- a/TimeSeriesAnalysis.Tests/Tests/GainSchedIdentifyTests.cs
+++ b/TimeSeriesAnalysis.Tests/Tests/GainSchedIdentifyTests.cs
@@ -15,6 +15,48 @@ public class GainSchedIdentifyTests
int timeBase_s = 1;
const double TimeConstantAllowedDev_s = 0.5;
+ [Test]
+ public void GainEstOnly_CorrectTresholdsGiven_CorrectGainsReturned()
+ {
+ int N = 100;
+
+ var gainSched_tenThresholds_singleInput = new GainSchedParameters
+ {
+ TimeConstant_s = null,
+ TimeConstantThresholds = null,
+ LinearGains = new List<double[]> { new double[] { 0 }, new double[] { 1 }, new double[] { 2 }, new double[] { 3 }, new double[] { 4 }, new double[] { 5 },
+ new double[] { 6 }, new double[] { 7 }, new double[] { 8 }, new double[] { 9 }, new double[] { 10 } },
+ LinearGainThresholds = new double[] { 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.5, 10.5 },
+ TimeDelay_s = 0,
+ Bias = 5,
+ GainSchedParameterIndex = 0
+ };
+
+ var refModel = new GainSchedModel(gainSched_tenThresholds_singleInput);
+ var gsFittingSpecs= new GainSchedFittingSpecs();
+ gsFittingSpecs.uGainThresholds = refModel.GetModelParameters().LinearGainThresholds;
+
+ var plantSim = new PlantSimulator(new List<ISimulatableModel> { refModel });
+ var inputData = new TimeSeriesDataSet();
+ var input = TimeSeriesCreator.ThreeSteps(N / 4, N * 2 / 4, N * 3 / 4, N, 0, 1, 2, 3).
+ Concat(TimeSeriesCreator.ThreeSteps(N / 4, N * 2 / 4, N * 3 / 4, N, 4, 5, 6, 7)).
+ Concat(TimeSeriesCreator.ThreeSteps(N / 4, N * 2 / 4, N * 3 / 4, N, 8, 9, 10, 11)).ToArray();
+ inputData.Add(plantSim.AddExternalSignal(refModel, SignalType.External_U, (int)INDEX.FIRST), input);
+ inputData.CreateTimestamps(timeBase_s);
+
+ // Act
+ var isSimulatable = plantSim.Simulate(inputData, out TimeSeriesDataSet simData);
+ Assert.IsTrue(isSimulatable);
+ var dataSet = new UnitDataSet();
+ dataSet.Y_meas = simData.GetValues(refModel.ID, SignalType.Output_Y);
+ dataSet.U = Array2D<double>.CreateFromList(new List<double[]> { inputData.GetValues(refModel.ID,SignalType.External_U)});
+
+ GainSchedIdentifier.IdentifyGainsForGivenThresholds(dataSet, gsFittingSpecs);
+
+ }
+
+
+
/*
[TestCase()]
public void ReturnsParametersWithNumberOfLinearGainsNotExceeding2()
@@ -82,7 +124,7 @@ public void ReturnsParametersWithNumberOfLinearGainsNotExceeding2()
}
*/
[TestCase()]
- public void GainEstimationOnly_GainsNotLargerThanTheBiggestPossibleGain()
+ public void GainAndThreshold_GainsNotLargerThanTheBiggestPossibleGain()
{
int N = 500;
@@ -161,7 +203,7 @@ public void GainEstimationOnly_GainsNotLargerThanTheBiggestPossibleGain()
[TestCase(5, 2.5)]
[TestCase(6, 3.0)]*/
[TestCase(7, 4.0)]
- public void ThresholdEstimation_LinearGainThresholdAtReasonablePlace(int ver, double gain_sched_threshold)
+ public void GainAndThreshold_LinearGainThresholdAtReasonablePlace(int ver, double gain_sched_threshold)
{
int N = 300;
// Arrange
@@ -231,11 +273,10 @@ public void ThresholdEstimation_LinearGainThresholdAtReasonablePlace(int ver, do
[TestCase(1, 35)]
[TestCase(38, 40)]
[TestCase(40, 20)]*/
- public void GainEstimationOnly_TwoGains_TimeConstantsAndThresholdFoundOk(double TimeConstant1_s, double TimeConstant2_s)
+ public void GainAndThreshold_TwoGains_TimeConstantsAndThresholdFoundOk(double TimeConstant1_s, double TimeConstant2_s)
{
int N = 300;
-
// Arrange
var unitData = new UnitDataSet("test");
double[] u1 = TimeSeriesCreator.ThreeSteps(N/5, N/3, N/2, N, -2, -1, 0, 1);
@@ -288,9 +329,6 @@ public void GainEstimationOnly_TwoGains_TimeConstantsAndThresholdFoundOk(double
}
-
-
-
/* Shared.EnablePlots();
Plot.FromList(new List<double[]> {
simY1,
@@ -309,7 +347,7 @@ public void GainEstimationOnly_TwoGains_TimeConstantsAndThresholdFoundOk(double
[TestCase(5, 3.5)]
[TestCase(6, 4.0)]*/
// [TestCase(7, 4.5)]
- public void ThresholdEstimation_ThresholdsWithinUminAndUmax(int ver, double gain_sched_threshold)
+ public void GainAndThreshold_ThresholdsWithinUminAndUmax(int ver, double gain_sched_threshold)
{
int N = 250;
// Arrange
@@ -449,5 +487,9 @@ public void GainSchedIdentify_AllTimeConstantsArePositive(int ver, double gain_s
// Shared.DisablePlots();
}
*/
+
+
+
+
}
}