public void VerifyROfRhoMonteCarloMeasuredNoNoiseMonteCarloModel()
{
var independentValues = new double[] { 1, 2, 3, 4, 5, 6 }; // rho [mm]
var actualProperties = new OpticalProperties(mua: 0.01, musp: 1.0, g: 0.8, n: 1.4);
var initialGuess = new OpticalProperties(mua: 0.02, musp: 1.2, g: 0.8, n: 1.4);
var simulatedMeasured = ComputationFactory.ComputeReflectance(
ForwardSolverType.MonteCarlo,
SolutionDomainType.ROfRho,
ForwardAnalysisType.R,
new object[] { new[] { actualProperties }, independentValues });
var standardDeviation = simulatedMeasured;
double[] fit = ComputationFactory.SolveInverse(
ForwardSolverType.MonteCarlo,
OptimizerType.MPFitLevenbergMarquardt,
SolutionDomainType.ROfRho,
simulatedMeasured,
standardDeviation,
InverseFitType.MuaMusp,
new object[] { new[] { initialGuess }, independentValues });
var convergedMua = fit[0];
var convergedMusp = fit[1];
Assert.Less(Math.Abs(convergedMua - 0.01), 1e-6);
Assert.Less(Math.Abs(convergedMusp - 1.0), 1e-6);
}
public void VerifyROfRhoMonteCarloMeasuredNoNoiseSDAModel()
{
var independentValues = new double[] { 10, 11, 12, 13, 14, 15 }; // rho [mm]
var actualProperties = new OpticalProperties(mua: 0.01, musp: 1.0, g: 0.8, n: 1.4);
var initialGuess = new OpticalProperties(mua: 0.02, musp: 1.2, g: 0.8, n: 1.4);
var lowerBounds = new double[] { 0, 0, 0, 0 };
var upperBounds = new double[] { double.PositiveInfinity, double.PositiveInfinity, double.PositiveInfinity, double.PositiveInfinity };
var simulatedMeasured = ComputationFactory.ComputeReflectance(
ForwardSolverType.MonteCarlo,
SolutionDomainType.ROfRho,
ForwardAnalysisType.R,
new object[] { new[] { actualProperties }, independentValues });
var standardDeviation = simulatedMeasured;
double[] fit = ComputationFactory.SolveInverse(
ForwardSolverType.DistributedPointSourceSDA,
OptimizerType.MPFitLevenbergMarquardt,
SolutionDomainType.ROfRho,
simulatedMeasured,
standardDeviation,
InverseFitType.MuaMusp,
new object[] { new[] { initialGuess }, independentValues },
lowerBounds,
upperBounds);
var convergedMua = fit[0];
var convergedMusp = fit[1];
Assert.Less(Math.Abs(convergedMua - 0.01), 0.002);
Assert.Less(Math.Abs(convergedMusp - 1.0), 0.11);
}
public void GetVectorizedIndependentVariableQueryNew_can_be_called_using_enum_inputs()
{
var test = ComputationFactory.ComputeReflectance(
ForwardSolverType.MonteCarlo,
SolutionDomainType.ROfRho,
ForwardAnalysisType.R,
new object[] { new[] { new OpticalProperties(0.01, 1, 0.8, 1.4) }, new double[] { 1, 2, 3 } });
}
public void validate_ROfRhoAndTime_With_Wavelength()
{
// used values for tissue=liver
var scatterer = new PowerLawScatterer(0.84, 0.55);
var hbAbsorber = new ChromophoreAbsorber(ChromophoreType.Hb, 66);
var hbo2Absorber = new ChromophoreAbsorber(ChromophoreType.HbO2, 124);
var fatAbsorber = new ChromophoreAbsorber(ChromophoreType.Fat, 0.02);
var waterAbsorber = new ChromophoreAbsorber(ChromophoreType.H2O, 0.87);
var n = 1.4;
var wvs = new double[] { 650, 700 };
var rhos = new double[] { 0.5, 1.625 };
var times = new double[] { 0.05, 0.10 };
var tissue = new Tissue(
new IChromophoreAbsorber[] { hbAbsorber, hbo2Absorber, fatAbsorber, waterAbsorber },
scatterer,
"test_tissue",
n);
var ops = wvs.Select(wv => tissue.GetOpticalProperties(wv)).ToArray();
var rVsWavelength = ComputationFactory.ComputeReflectance(
new PointSourceSDAForwardSolver(),
SolutionDomainType.ROfRhoAndTime,
ForwardAnalysisType.R,
new object[]
{
ops,
rhos,
times
});
// return from ROfRhoAndTime is new double[ops.Length * rhos.Length * ts.Length];
// order is: (ops0,rhos0,ts0), (ops0,rhos0,ts1)...(ops0,rhos0,tsnt-1)
// (ops0,rhos1,ts0), (ops0,rhos1,ts1)...(ops0,rhos1,tsnt-1)
// ...
// (ops0,rhosnr-1,ts0),.................(ops0,rhosnr-1,tsnt-1)
// ... repeat above with ops1...
// [0] -> ops0=650, rho0=0.5, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[0] - 0.044606) < 0.000001); // API match
// [1] -> ops0=650, rho0=0.5, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[1] - 0.005555) < 0.000001);
// [2] -> ops0=650, rho1=1.635, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[2] - 0.036900) < 0.000001); // API match
// [3] -> ops0=650, rho1=1.635, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[3] - 0.005053) < 0.000001);
// [4] -> ops1=700, rho0=0.5, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[4] - 0.057894) < 0.000001); // API match
// [5] -> ops1=700, rho0=0.5, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[5] - 0.010309) < 0.000001);
// [6] -> ops1=700, rho1=1.635, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[6] - 0.048493) < 0.000001); // API match
// [7] -> ops1=700, rho1=1.635, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[7] - 0.009434) < 0.000001);
}
public void validate_ROfFxAndTime_With_Wavelength()
{
// used values for tissue=liver
var scatterer = new PowerLawScatterer(0.84, 0.55);
var hbAbsorber = new ChromophoreAbsorber(ChromophoreType.Hb, 66);
var hbo2Absorber = new ChromophoreAbsorber(ChromophoreType.HbO2, 124);
var fatAbsorber = new ChromophoreAbsorber(ChromophoreType.Fat, 0.02);
var waterAbsorber = new ChromophoreAbsorber(ChromophoreType.H2O, 0.87);
var n = 1.4;
var wvs = new double[] { 650, 700 };
var fxs = new double[] { 0.0, 0.5 };
var times = new double[] { 0.05, 0.10 };
var tissue = new Tissue(
new IChromophoreAbsorber[] { hbAbsorber, hbo2Absorber, fatAbsorber, waterAbsorber },
scatterer,
"test_tissue",
n);
var ops = wvs.Select(wv => tissue.GetOpticalProperties(wv)).ToArray();
var rVsWavelength = ComputationFactory.ComputeReflectance(
new DistributedPointSourceSDAForwardSolver(),
SolutionDomainType.ROfFxAndTime,
ForwardAnalysisType.R,
new object[]
{
ops,
fxs,
times
});
// return from ROfFxAndTime is new double[ops.Length * fxs.Length * ts.Length];
// order is: (ops0,fxs0,ts0), (ops0,fxs0,ts1)...(ops0,fxs0,tsnt-1)
// (ops0,fxs1,ts0), (ops0,fxs1,ts1)...(ops0,fxs1,tsnt-1)
// ...
// (ops0,fxsnf-1,ts0),................(ops0,fxsnf-1,tsnt-1)
// ... repeat above with ops1...
// [0] -> ops0=650, fx0=0.0, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[0] - 1.558702) < 0.000001);
// [1] -> ops0=650, fx0=0.0, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[1] - 0.391871) < 0.000001);
// [2] -> ops0=650, fx1=0.5, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[2] - 5.023055e-12) < 0.000001e-12);
// [3] -> ops0=650, fx1=0.5, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[3] - 1.032586e-13) < 0.000001e-13);
// [4] -> ops1=700, fx0=0.0, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[4] - 2.218329) < 0.000001);
// [5] -> ops1=700, fx1=0.5, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[5] - 0.797200) < 0.000001);
// [6] -> ops1=700, fx0=0.0, ts0=0.05
Assert.IsTrue(Math.Abs(rVsWavelength[6] - 1.347053e-12) < 0.000001e-12);
// [7] -> ops1=700, fx1=0.5, ts1=0.10
Assert.IsTrue(Math.Abs(rVsWavelength[7] - 2.052883e-13) < 0.000001e-13);
}
public InverseSolutionResult SolveInverse()
{
var lowerBounds = new double[] { 0, 0, 0, 0 };
var upperBounds = new double[] { double.PositiveInfinity, double.PositiveInfinity, double.PositiveInfinity, double.PositiveInfinity };
var measuredOpticalProperties = GetMeasuredOpticalProperties();
var measuredDataValues = GetSimulatedMeasuredData();
var dependentValues = measuredDataValues.ToArray();
var initGuessOpticalProperties = GetInitialGuessOpticalProperties();
var initGuessParameters = GetParametersInOrder(initGuessOpticalProperties);
// replace unconstrained L-M optimization with constrained version
// this solves problem of when distributed source solution produces neg OPs during inversion
//var fit = ComputationFactory.SolveInverse(
// InverseForwardSolverTypeOptionVM.SelectedValue,
// OptimizerTypeOptionVM.SelectedValue,
// SolutionDomainTypeOptionVM.SelectedValue,
// dependentValues,
// dependentValues, // set standard deviation, sd, to measured (works w/ or w/o noise)
// InverseFitTypeOptionVM.SelectedValue,
// initGuessParameters.Values.ToArray());
var fit = ComputationFactory.SolveInverse(
InverseForwardSolverTypeOptionVM.SelectedValue,
OptimizerTypeOptionVM.SelectedValue,
SolutionDomainTypeOptionVM.SelectedValue,
dependentValues,
dependentValues, // set standard deviation, sd, to measured (works w/ or w/o noise)
InverseFitTypeOptionVM.SelectedValue,
initGuessParameters.Values.ToArray(),
lowerBounds, upperBounds);
var fitOpticalProperties = ComputationFactory.UnFlattenOpticalProperties(fit);
var fitParameters = GetParametersInOrder(fitOpticalProperties);
var resultDataValues = ComputationFactory.ComputeReflectance(
InverseForwardSolverTypeOptionVM.SelectedValue,
SolutionDomainTypeOptionVM.SelectedValue,
ForwardAnalysisType.R,
fitParameters.Values.ToArray());
var resultDataPoints = GetDataPoints(resultDataValues);
return(new InverseSolutionResult
{
FitDataPoints = resultDataPoints,
MeasuredOpticalProperties = (OpticalProperties[])measuredOpticalProperties,
// todo: currently only supports homog OPs
GuessOpticalProperties = (OpticalProperties[])initGuessOpticalProperties,
// todo: currently only supports homog OPss
FitOpticalProperties = fitOpticalProperties
});
}
public double[] CalculateInitialGuess()
{
var opticalProperties = GetInitialGuessOpticalProperties();
var parameters = GetParametersInOrder(opticalProperties);
return ComputationFactory.ComputeReflectance(
InverseForwardSolverTypeOptionVM.SelectedValue,
SolutionDomainTypeOptionVM.SelectedValue,
ForwardAnalysisType.R,
parameters.Values.ToArray());
}
public void validate_ComputeReflectance_can_be_called_using_IForwardSolver()
{
var reflectance = ComputationFactory.ComputeReflectance(
new NurbsForwardSolver(),
SolutionDomainType.ROfFx,
ForwardAnalysisType.dRdMua,
new object[]
{
new [] { new OpticalProperties(0.01, 1, 0.8, 1.4) },
new double[] { 1, 2, 3 }
});
Assert.IsTrue(Math.Abs(reflectance[0] + 0.005571) < 0.000001);
}
private double[] GetSimulatedMeasuredData()
{
var opticalProperties = GetMeasuredOpticalProperties();
var parameters = GetParametersInOrder(opticalProperties);
var measuredData = ComputationFactory.ComputeReflectance(
MeasuredForwardSolverTypeOptionVM.SelectedValue,
SolutionDomainTypeOptionVM.SelectedValue,
ForwardAnalysisType.R,
parameters.Values.ToArray());
return measuredData.AddNoise(PercentNoise);
}
public IDataPoint[][] ExecuteForwardSolver()
{
var opticalProperties = GetOpticalProperties();
var parameters = GetParametersInOrder(opticalProperties);
var reflectance = ComputationFactory.ComputeReflectance(
ForwardSolverTypeOptionVM.SelectedValue,
SolutionDomainTypeOptionVM.SelectedValue,
ForwardAnalysisTypeOptionVM.SelectedValue,
parameters.Values.ToArray());
return(GetDataPoints(reflectance));
}
public void validate_ComputeReflectance_can_be_called_using_enum_forward_solver()
{
var reflectance = ComputationFactory.ComputeReflectance(
ForwardSolverType.MonteCarlo,
SolutionDomainType.ROfRho,
ForwardAnalysisType.R,
new object[]
{
// could have array of OPs, one set for each tissue region
new[] { new OpticalProperties(0.01, 1, 0.8, 1.4) },
new double[] { 1, 2, 3 }
});
Assert.IsTrue(Math.Abs(reflectance[0] - 0.021093) < 0.000001);
}
public InverseSolutionResult SolveInverse()
{
var measuredOpticalProperties = GetMeasuredOpticalProperties();
var measuredDataValues = GetSimulatedMeasuredData();
var dependentValues = measuredDataValues.ToArray();
var initGuessOpticalProperties = GetInitialGuessOpticalProperties();
var initGuessParameters = GetParametersInOrder(initGuessOpticalProperties);
double[] fit = ComputationFactory.SolveInverse(
InverseForwardSolverTypeOptionVM.SelectedValue,
OptimizerTypeOptionVM.SelectedValue,
SolutionDomainTypeOptionVM.SelectedValue,
dependentValues,
dependentValues, // set standard deviation, sd, to measured (works w/ or w/o noise)
InverseFitTypeOptionVM.SelectedValue,
initGuessParameters.Values.ToArray());
var fitOpticalProperties = ComputationFactory.UnFlattenOpticalProperties(fit);
var fitParameters = GetParametersInOrder(fitOpticalProperties);
var resultDataValues = ComputationFactory.ComputeReflectance(
InverseForwardSolverTypeOptionVM.SelectedValue,
SolutionDomainTypeOptionVM.SelectedValue,
ForwardAnalysisType.R,
fitParameters.Values.ToArray());
var resultDataPoints = GetDataPoints(resultDataValues);
return new InverseSolutionResult
{
FitDataPoints = resultDataPoints,
MeasuredOpticalProperties = (OpticalProperties[])measuredOpticalProperties, // todo: currently only supports homog OPs
GuessOpticalProperties = (OpticalProperties[])initGuessOpticalProperties, // todo: currently only supports homog OPss
FitOpticalProperties = fitOpticalProperties
};
}
public void validate_ROfFxAndFt_With_Wavelength()
{
// used values for tissue=liver
var scatterer = new PowerLawScatterer(0.84, 0.55);
var hbAbsorber = new ChromophoreAbsorber(ChromophoreType.Hb, 66);
var hbo2Absorber = new ChromophoreAbsorber(ChromophoreType.HbO2, 124);
var fatAbsorber = new ChromophoreAbsorber(ChromophoreType.Fat, 0.02);
var waterAbsorber = new ChromophoreAbsorber(ChromophoreType.H2O, 0.87);
var n = 1.4;
var wvs = new double[] { 650, 700 };
var fxs = new double[] { 0.0, 0.5 };
var fts = new double[] { 0.0, 0.50 };
var tissue = new Tissue(
new IChromophoreAbsorber[] { hbAbsorber, hbo2Absorber, fatAbsorber, waterAbsorber },
scatterer,
"test_tissue",
n);
var ops = wvs.Select(wv => tissue.GetOpticalProperties(wv)).ToArray();
var rVsWavelength = ComputationFactory.ComputeReflectance(
new DistributedPointSourceSDAForwardSolver(),
SolutionDomainType.ROfFxAndFt,
ForwardAnalysisType.R,
new object[]
{
ops,
fxs,
fts
});
// return from ROfFxAndFt is new double[ops.Length * fxs.Length * fts.Length];
// order is: (ops0,fxs0,fts0)real, (ops0,fxs0,ts1)real...(ops0,fxs0,ftsnt-1)real
// (ops0,fxs1,fts0)real, (ops0,fxs1,ts1)real...(ops0,fxs1,ftsnt-1)real
// ...
// (ops0,fxsnf-1,fts0)real,.................(ops0,fxsnf-1,ftsnt-1)real
// ... repeat above with imag, then with ops1...
// [0] -> ops0=650, fx0=0.0, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[0] - 1.890007) < 0.000001); // API match
// [1] -> ops0=650, fx0=0.0, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[1] - 1.888160) < 0.000001);
// [2] -> ops0=650, fx1=0.5, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[2] - 0.562537) < 0.000001); // API match
// [3] -> ops0=650, fx1=0.5, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[3] - 0.562543) < 0.000001);
// [4] -> ops1=700, fx0=0.0, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[4] - 2.118427) < 0.000001); // API match
// [5] -> ops1=700, fx0=0.0, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[5] - 2.113377) < 0.000001);
// [6] -> ops1=700, fx1=0.5, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[6] - 0.543539) < 0.000001); // API match
// [7] -> ops1=700, fx1=0.5, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[7] - 0.543546) < 0.000001);
// [8] -> ops0=650, fx0=0.0, fts0=0.0 imag
Assert.IsTrue(Math.Abs(rVsWavelength[8] - 0.0) < 0.000001); // API match
// [9] -> ops0=650, fx0=0.0, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[9] + 0.045122) < 0.000001);
// [10] -> ops0=650, fx1=0.5, fts0=0.0 imag
Assert.IsTrue(Math.Abs(rVsWavelength[10] - 0.0) < 0.000001); // API match
// [11] -> ops0=650, fx1=0.5, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[11] + 0.000799) < 0.000001);
// [12] -> ops1=700, fx0=0.0, fts0=0.0 imag
Assert.IsTrue(Math.Abs(rVsWavelength[12] - 0.0) < 0.000001); // API match
// [13] -> ops1=700, fx0=0.0, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[13] + 0.071758) < 0.000001);
// [14] -> ops1=700, fx1=0.5, fts0=0.0 imag
Assert.IsTrue(Math.Abs(rVsWavelength[14] - 0.0) < 0.000001); // API match
// [15] -> ops1=700, fx1=0.5, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[15] + 0.000651) < 0.000001);
}
public void validate_ROfRhoAndFt_With_Wavelength()
{
// used values for tissue=liver
var scatterer = new PowerLawScatterer(0.84, 0.55);
var hbAbsorber = new ChromophoreAbsorber(ChromophoreType.Hb, 66);
var hbo2Absorber = new ChromophoreAbsorber(ChromophoreType.HbO2, 124);
var fatAbsorber = new ChromophoreAbsorber(ChromophoreType.Fat, 0.02);
var waterAbsorber = new ChromophoreAbsorber(ChromophoreType.H2O, 0.87);
var n = 1.4;
var wvs = new double[] { 650, 700 };
var rhos = new double[] { 0.5, 1.625 };
var fts = new double[] { 0.0, 0.50 };
var tissue = new Tissue(
new IChromophoreAbsorber[] { hbAbsorber, hbo2Absorber, fatAbsorber, waterAbsorber },
scatterer,
"test_tissue",
n);
var ops = wvs.Select(wv => tissue.GetOpticalProperties(wv)).ToArray();
var rVsWavelength = ComputationFactory.ComputeReflectance(
new PointSourceSDAForwardSolver(),
SolutionDomainType.ROfRhoAndFt,
ForwardAnalysisType.R,
new object[]
{
ops,
rhos,
fts
});
// return from ROfRhoAndFt is new double[ops.Length * rhos.Length * fts.Length];
// order is: (ops0,rhos0,fts0)real, (ops0,rhos0,fts1)real...(ops0,rhos0,ftsnt-1)real
// (ops0,rhos1,fts0)real, (ops0,rhos1,fts1)real...(ops0,rhos1,ftsnt-1)real
// ...
// (ops0,rhosnr-1,fts0)real,.................(ops0,rhosnr-1,ftsnt-1)real
// ... repeat above with imag, then next ops1...
// [0] -> ops0=650, rho0=0.5, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[0] - 0.037575) < 0.000001);
// [1] -> ops0=650, rho0=0.5, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[1] - 0.037511) < 0.000001);
// [2] -> ops0=650, rho1=1.635, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[2] - 0.009306) < 0.000001);
// [3] -> ops0=650, rho1=1.635, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[3] - 0.009255) < 0.000001);
// [4] -> ops1=700, rho0=0.5, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[4] - 0.036425) < 0.000001);
// [5] -> ops1=700, rho0=0.5, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[5] - 0.036310) < 0.000001);
// [6] -> ops1=700, rho1=1.635, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[6] - 0.010657) < 0.000001);
// [7] -> ops1=700, rho1=1.635, fts1=0.5 real
Assert.IsTrue(Math.Abs(rVsWavelength[7] - 0.010558) < 0.000001);
// [8] -> ops0=650, rho0=0.5, fts0=0.0 imag
Assert.IsTrue(Math.Abs(rVsWavelength[8] - 0.0) < 0.000001);
// [9] -> ops0=650, rho0=0.5, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[9] + 0.001200) < 0.000001);
// [10] -> ops0=650, rho1=1.635, fts0=0.0 imag
Assert.IsTrue(Math.Abs(rVsWavelength[10] - 0.0) < 0.000001);
// [11] -> ops1=650, rho1=1.635, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[11] + 0.000674) < 0.000001);
// [12] -> ops1=700, rho0=0.5, fts0=0.0
Assert.IsTrue(Math.Abs(rVsWavelength[12] - 0.0) < 0.000001);
// [13] -> ops1=700, rho0=0.5, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[13] + 0.001446) < 0.000001);
// [14] -> ops1=700, rho1=1.635, fts0=0.0 real
Assert.IsTrue(Math.Abs(rVsWavelength[14] - 0.0) < 0.000001);
// [15] -> ops1=700, rho1=1.635, fts1=0.5 imag
Assert.IsTrue(Math.Abs(rVsWavelength[15] + 0.000929) < 0.000001);
}
public string Plot(IPlotParameters plotParameters)
{
var parameters = (SolutionDomainPlotParameters)plotParameters;
var fs = parameters.ForwardSolverType;
var op = parameters.OpticalProperties;
var independentValue = parameters.IndependentAxes.Value;
var independentValues = parameters.XAxis.AsEnumerable().ToArray();
try
{
Plots plot;
var parametersInOrder = _parameterTools.GetParametersInOrder(
_parameterTools.GetOpticalPropertiesObject(parameters.OpticalProperties),
plotParameters.XAxis.AsEnumerable().ToArray(),
parameters.SolutionDomain,
parameters.IndependentAxes.Label,
parameters.IndependentAxes.Value);
var parametersInOrderObject = parametersInOrder.Values.ToArray();
var reflectance = parameters.NoiseValue > 0 ? ComputationFactory.ComputeReflectance(fs, parameters.SolutionDomain, parameters.ModelAnalysis, parametersInOrderObject).AddNoise(parameters.NoiseValue) : ComputationFactory.ComputeReflectance(fs, parameters.SolutionDomain, parameters.ModelAnalysis, parametersInOrderObject);
var isComplex = ComputationFactory.IsComplexSolver(parameters.SolutionDomain);
var hasIndependentAxis = parameters.SolutionDomain != SolutionDomainType.ROfFx && parameters.SolutionDomain != SolutionDomainType.ROfRho;
if (!isComplex)
{
var xyPoints = independentValues.Zip(reflectance, (x, y) => new Point(x, y));
var plotData = new PlotData {
Data = xyPoints, Label = parameters.SolutionDomain.ToString()
};
plot = new Plots {
Id = hasIndependentAxis ? $"{parameters.SolutionDomain.ToString()}Fixed{parameters.IndependentAxes.Label}" : $"{parameters.SolutionDomain.ToString()}",
PlotList = new List <PlotDataJson>()
};
plot.PlotList.Add(new PlotDataJson {
Data = plotData.Data.Select(item => new List <double> {
item.X, item.Y
}).ToList(),
Label = hasIndependentAxis ? $"{fs} μa={op.Mua} μs'={op.Musp} {parameters.IndependentAxes.Label}={parameters.IndependentAxes.Value}" : $"{fs} μa={op.Mua} μs'={op.Musp}"
});
}
else
{
var offset = reflectance.Length / 2;
IEnumerable <ComplexPoint> xyPointsComplex = independentValues.Zip(reflectance, (x, y) => new ComplexPoint(x, new Complex(y, reflectance[Array.IndexOf(reflectance, y) + offset]))).ToArray();
var xyPointsReal = xyPointsComplex.Select(item => new Point(item.X, item.Y.Real));
var xyPointsImaginary = xyPointsComplex.Select(item => new Point(item.X, item.Y.Imaginary));
var plotDataReal = new PlotData {
Data = xyPointsReal, Label = parameters.SolutionDomain.ToString()
};
var plotDataImaginary = new PlotData {
Data = xyPointsImaginary, Label = parameters.SolutionDomain.ToString()
};
plot = new Plots {
Id = $"{parameters.SolutionDomain.ToString()}Fixed{parameters.IndependentAxes.Label}",
PlotList = new List <PlotDataJson>()
};
plot.PlotList.Add(new PlotDataJson {
Data = plotDataReal.Data.Select(item => new List <double> {
item.X, item.Y
}).ToList(),
Label = $"{fs} μa={op.Mua} μs'={op.Musp} {parameters.IndependentAxes.Label}={independentValue}(real)"
});
plot.PlotList.Add(new PlotDataJson {
Data = plotDataImaginary.Data.Select(item => new List <double> {
item.X, item.Y
}).ToList(),
Label = $"{fs} μa={op.Mua} μs'={op.Musp} {parameters.IndependentAxes.Label}={independentValue}(imag)"
});
}
var msg = JsonConvert.SerializeObject(plot);
return(msg);
}
catch (Exception e)
{
_logger.LogError("An error occurred: {Message}", e.Message);
throw;
}
}