Updated the PHD plots to use all Rho values

Author: lmalenfant

forward-solvers/phd-of-rho-and-z-two-layer-compute-fluence.py

@@ -33,8 +33,6 @@
 solver = TwoLayerSDAForwardSolver()
 solver.SourceConfiguration = SourceConfiguration.Distributed
 
-distributedSolver = DistributedPointSourceSDAForwardSolver()
-
 topLayerThickness = 5
 opRegions = Array.CreateInstance(IOpticalPropertyRegion, 2)
 opRegions[0] = LayerOpticalPropertyRegion(DoubleRange(0, topLayerThickness, 2), OpticalProperties(0.1, 1, 0.8, 1.4))
@@ -58,38 +56,33 @@
 zs = 0.1 + zs_delta * np.arange(100)
 print(zs)
 
+allRhos = np.concatenate((-rhos[::-1], rhos))
+print("*********************************** RHOS *****************************************")
+print(allRhos.tolist())
+
 opRegionsArray = Array[Array[IOpticalPropertyRegion]]([opRegions])
 # predict the tissue's fluence(rho, z) for the given optical properties 
-fluence = solver.FluenceOfRhoAndZ(opRegionsArray, rhos, zs );
 independentAxes = Array.CreateInstance(IndependentVariableAxis, 1)
 independentAxes[0] = IndependentVariableAxis.Z
 independentValues = Array.CreateInstance(Array[Double], 2)
-independentValues[0] = Array[Double](rhos.tolist())
+independentValues[0] = Array[Double](allRhos.tolist())
 independentValues[1] = Array[Double](zs.tolist())
-fluenceOfRhoAndZ = ComputationFactory.ComputeFluence(distributedSolver, FluenceSolutionDomainType.FluenceOfRhoAndZ, independentAxes, independentValues, opRegions, Array[Double](rhos.tolist()))
+fluenceOfRhoAndZ = ComputationFactory.ComputeFluence(solver, FluenceSolutionDomainType.FluenceOfRhoAndZ, independentAxes, independentValues, opRegions, Array[Double](allRhos.tolist()))
 
 #PHD
 sourceDetectorSeparation = 10
 opArray = Array.CreateInstance(OpticalProperties, 2)
 opArray[0] = OpticalProperties(0.1, 1, 0.8, 1.4)
 opArray[1] = OpticalProperties(0.01, 1, 0.8, 1.4)
 
-phdOfRhoAndZ = ComputationFactory.GetPHD(ForwardSolverType.TwoLayerSDA, fluence, sourceDetectorSeparation, opArray, Array[Double](rhos.tolist()), Array[Double](zs.tolist()))
-
-allRhos = np.concatenate((-rhos[::-1], rhos))
-print("*********************************** RHOS *****************************************")
-print(allRhos.tolist())
+phdOfRhoAndZ = ComputationFactory.GetPHD(ForwardSolverType.TwoLayerSDA, fluenceOfRhoAndZ, sourceDetectorSeparation, opArray, Array[Double](allRhos.tolist()), Array[Double](zs.tolist()))
 
 # log transform
 log_phd = [Math.Log(f) for f in phdOfRhoAndZ]
-log_fluence = [Math.Log(f) for f in fluenceOfRhoAndZ]
 
 size = len(zs)
 # split into rows
 phdRowsToPlot = np.array([log_phd[i:i+size] for i in range(0, len(log_phd), size)])
-fluenceRowsToPlot = np.array([log_fluence[i:i+size] for i in range(0, len(log_fluence), size)])
-# reverse and concatenate
-allFluenceRowsToPlot = np.concatenate((fluenceRowsToPlot[::-1], phdRowsToPlot))
 
 def heatmap(values, x, y, x_label="", y_label="", title=""):
     """Create a heatmap chart."""
@@ -110,5 +103,5 @@ def heatmap(values, x, y, x_label="", y_label="", title=""):
     )
     return fig
 
-fluenceChart = heatmap(allFluenceRowsToPlot.tolist(), allRhos.tolist(), list(zs), "ρ [mm]", "z [mm]", "log(phd(ρ, z) [mm-2])")
+fluenceChart = heatmap(phdRowsToPlot.tolist(), allRhos.tolist(), list(zs), "ρ [mm]", "z [mm]", "log(phd(ρ, z) [mm-2])")
 fluenceChart.show(renderer="browser")

forward-solvers/phd-of-rho-and-z-two-layer.py

@@ -103,5 +103,5 @@ def heatmap(values, x, y, x_label="", y_label="", title=""):
     )
     return fig
 
-fluenceChart = heatmap(fluenceRowsToPlot.tolist(), list(rhos), list(zs), "ρ [mm]", "z [mm]", "log(phd(ρ, z) [mm-2])")
+fluenceChart = heatmap(fluenceRowsToPlot.tolist(), allRhos.tolist(), list(zs), "ρ [mm]", "z [mm]", "log(phd(ρ, z) [mm-2])")
 fluenceChart.show(renderer="browser")