From 5750a30b68b8200a5c733f9873afa72a2d7a2e31 Mon Sep 17 00:00:00 2001
From: Mikhail Svechnikov <m.svechnikov@fz-juelich.de>
Date: Thu, 29 Aug 2024 16:07:17 +0200
Subject: [PATCH] rm SliceInterface
---
.../RoughMultiLayerContribution.cpp | 28 ++++++-------------
1 file changed, 8 insertions(+), 20 deletions(-)
diff --git a/Sim/Computation/RoughMultiLayerContribution.cpp b/Sim/Computation/RoughMultiLayerContribution.cpp
index 73d64e8d6a3..091e474fa95 100644
--- a/Sim/Computation/RoughMultiLayerContribution.cpp
+++ b/Sim/Computation/RoughMultiLayerContribution.cpp
@@ -100,18 +100,6 @@ complex_t get_sum8terms(const ReSample& re_sample, size_t i_layer, const Diffuse
return term1 + term2 + term3 + term4 + term5 + term6 + term7 + term8;
}
-class SliceInterface {
-public:
- SliceInterface(const Slice& slice)
- : hig(slice.hig())
- , topRoughness(slice.topRoughness())
- {
- ASSERT(topRoughness);
- }
- double hig = 0;
- const LayerRoughness* topRoughness = nullptr;
-};
-
} // namespace
double Compute::roughMultiLayerContribution(const ReSample& re_sample, const DiffuseElement& ele)
@@ -125,7 +113,7 @@ double Compute::roughMultiLayerContribution(const ReSample& re_sample, const Dif
double autocorr_sum = 0;
double crosscorr_sum = 0;
- std::vector<SliceInterface> roughStack; // only slices with rough top interfaces
+ std::vector<Slice> roughStack; // only slices with rough top interfaces
std::vector<complex_t> rterm;
std::vector<complex_t> sterm;
@@ -146,12 +134,12 @@ double Compute::roughMultiLayerContribution(const ReSample& re_sample, const Dif
// precompute autocorrelation terms
for (int i = n_interfaces - 1; i >= 0; i--) {
- auto* autocorr_model = roughStack[i].topRoughness->autocorrelationModel();
+ auto* autocorr_model = roughStack[i].topRoughness()->autocorrelationModel();
if (auto* k_corr = dynamic_cast<const K_CorrelationModel*>(autocorr_model)) {
spectrum[i] = k_corr->spectralFunction(q);
} else if (auto* lin_growth = dynamic_cast<const LinearGrowthModel*>(autocorr_model)) {
ASSERT(i < int(n_interfaces - 1));
- const double thickness = roughStack[i].hig - roughStack[i + 1].hig;
+ const double thickness = roughStack[i].hig() - roughStack[i + 1].hig();
spectrum[i] = lin_growth->spectralFunction(spectrum[i + 1], thickness, q);
}
}
@@ -162,15 +150,15 @@ double Compute::roughMultiLayerContribution(const ReSample& re_sample, const Dif
// precompute crosscorrelation terms
for (int j = n_interfaces - 2; j >= 0; j--) {
- const double thickness = roughStack[j].hig - roughStack[j + 1].hig;
+ const double thickness = roughStack[j].hig() - roughStack[j + 1].hig();
if (auto* spat_freq_cc = dynamic_cast<const SpatialFrequencyCrosscorrelation*>(
- roughStack[j].topRoughness->crosscorrelationModel())) {
- const double sigma_up = roughStack[j].topRoughness->sigma();
- const double sigma_low = roughStack[j + 1].topRoughness->sigma();
+ roughStack[j].topRoughness()->crosscorrelationModel())) {
+ const double sigma_up = roughStack[j].topRoughness()->sigma();
+ const double sigma_low = roughStack[j + 1].topRoughness()->sigma();
crosscorr_with_interface_below[j] = spat_freq_cc->crosscorrSpectrum(
sigma_up, sigma_low, spectrum[j], spectrum[j + 1], thickness, q);
} else if (auto* lin_growth_autocorr = dynamic_cast<const LinearGrowthModel*>(
- roughStack[j].topRoughness->autocorrelationModel())) {
+ roughStack[j].topRoughness()->autocorrelationModel())) {
crosscorr_with_interface_below[j] =
lin_growth_autocorr->crosscorrSpectrum(spectrum[j + 1], thickness, q);
}
--
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